{ "row": "coworker-bossware-database", "entity": "coworker-bossware-database", "address": "Bossware and Employment Tech Database", "addresses": [ { "address": "Bossware and Employment Tech Database", "slug": "bossware-and-employment-tech-database-aio-20261029", "addr_id": "ADDR-bc5215fba8fa", "obs_id": "OBS-ac3acd79e5f3", "axn": "AXN:0AE9.CAPTURE.👁️🔍🔄🔆🏔️♌" } ], "epoch": "2026-10-29", "type": "C (public entity on which the archive bears: a database of workplace technology products; an entity of the Labor Vector meta-aggregator)", "surface": "Google AI Overview (expanded)", "auth": "signed out, incognito", "status": { "procedure": "EA-NEGONT-02 v0.9, #1690: equal case, ρ = extends, read from the Labor Vector census record, the capture record and the deposit bearing on the class (#747); archive selected by D/R/O (1 deposit admitted by reading at O-class of 2 string-pass deposits; hop of 2 read and rejected; 6 further deposits read outside the pass and rejected), with the census record (31 claims) and the Capture Registry's findings, reading, analysis, query note and PER notes (13 claims) ledgered as the archive's records of the entity; the field B by three origins (8 cards, 5 of them unreachable and 1 fetched with its title only; 1 own page; Wikipedia, no article); the composer read the ledgers, never the transcript, except where the brief asks for T's claims and the delta", "ledger": "unaudited (§3.8: one extractor per ledger); field quotes 56/56 verified by script against the saved texts, the Wikipedia response summary or the card text; archive quotes 51/51 verified against the registry, census.json and the deposit text", "frozen": false, "breaches": [] }, "spec": "EA-NEGONT-02 v0.9, #1690", "objects": { "T": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/T1-bossware-and-employment-tech-database-aio-20261029.txt", "sha256": "2e8502f0257c95f6074513071bcc9854b9ab3af0a826be0191f40e972a9c5111", "words": 231, "cards": 8, "words_note": "one transcript at one address (231 words in the answer body with its closer, links reduced to their text, markers and the card rail excluded; 8 cards)", "claims": [ "T1-1 definition: 'The Coworker.org Bossware and Employment Tech Database catalogs more than 550 labor-focused technology products used to monitor, track, and manage workers across various industries.' (inline link and one marker, both the token of card 1)", "T1-2 the term: '\"Bossware\" refers to software and digital tools that managers use to supervise employee habits, outputs, physical locations, and biometrics.' (one marker, an unresolved token)", "T1-3 activity tracking: 'Activity Tracking: Logging keystrokes, mouse movements, active window focus, and app or website usage.' (two markers, unresolved tokens)", "T1-4 visual monitoring: 'Visual Monitoring: Taking periodic or continuous screenshots and recording webcams.' (two markers, unresolved tokens)", "T1-5 location and biometrics: 'Location & Biometrics: Tracking real-time GPS locations, facial recognition, or physical movement metrics.' (two markers: an unresolved token and card 1's)", "T1-6 productivity scoring: 'Productivity Scoring: Generating automated daily scores or flagged alerts for \"productive\" versus \"unproductive\" behavior.' (two markers: card 3's token and an unresolved token)", "T1-7 the database as current: 'The Coworker Worktech Database tracks a wide range of platforms across categories' (inline link and one marker, card 1's token)", "T1-8 monitoring examples: 'Productivity & Monitoring Software: ActivTrak, Hubstaff, Time Doctor, Desklog, and Controlio.' (three markers: card 1's, card 2's and an unresolved token)", "T1-9 industry examples: 'Industry-Specific & Logistics Tracking: Amazon internal tools (such as Project Ultraviolet, Mentor App, and WiFi Tracking), Alice Housekeeping (hotel worker tracking), and Netradyne (fleet/driver monitoring).' (one marker, card 1's token)", "T1-10 hiring examples: 'Hiring & AI Analytics: HireVue (voice and interview analysis), Arctic Shores (behavioral hiring assessments), and Arya (AI recruiting).' (two markers: card 1's and card 3's tokens)", "T1-11 privacy: 'Research highlighted by institutions like Vanderbilt Law School shows that many workplace monitoring apps collect deep data profiles (including personal emails, device data, and location records) and share them with third-party tech and advertising domains.' (inline link and one marker, card 2's token)", "T1-12 closer: 'Would you like to search for information on specific monitoring tools, state disclosure laws, or how to audit what software is running on a device?'" ], "register": { "register": "data/EA-WG-CAPTURES-01.json", "slug": "bossware-and-employment-tech-database-aio-20261029", "obs_id": "OBS-ac3acd79e5f3" }, "transcripts": [ { "address": "Bossware and Employment Tech Database", "slug": "bossware-and-employment-tech-database-aio-20261029", "addr_id": "ADDR-bc5215fba8fa", "obs_id": "OBS-ac3acd79e5f3", "axn": "AXN:0AE9.CAPTURE.👁️🔍🔄🔆🏔️♌", "date": "2026-10-29", "surface": "Google AI Overview (expanded)", "auth": "signed out, incognito", "sha256": "2e8502f0257c95f6074513071bcc9854b9ab3af0a826be0191f40e972a9c5111", "sha256_of": "the registry's 'transcript' string (utf-8)", "sha256_raw": "0d4358bdcb981ce4066c35e1ba3af4f10937f98bd8a60b34092b28a400a43b9b", "words": 231, "cards": 8, "card_rail": [ "1. home.coworker.org — Bossware and Employment Tech Database - Coworker", "2. Vanderbilt Law School — Bossware Is Spying on Workers and Sharing Their Data | Vanderbilt Law School | Vanderbilt University", "3. Facebook·Ronan Farrow — Bossware Workplace Surveillance: 70% of U.S. Employers Track Workers", "4. YouTube·media.ccc.de — Pwning Bossware for Fun and Ethics", "5. The New York Times — Are ‘Bossware’ Tools Tracking You? - The New York Times", "6. YouTube·Bloomberg Originals — How Bossware is Watching While You Work", "7. YouTube·Kyla Scanlon — What's the Deal with Bossware?", "8. YouTube·PDQ — Is your boss watching you right now? 👁️ #bossware #privacy #worklife" ], "claims": [ "T1-1 definition: 'The Coworker.org Bossware and Employment Tech Database catalogs more than 550 labor-focused technology products used to monitor, track, and manage workers across various industries.' (inline link and one marker, both the token of card 1)", "T1-2 the term: '\"Bossware\" refers to software and digital tools that managers use to supervise employee habits, outputs, physical locations, and biometrics.' (one marker, an unresolved token)", "T1-3 activity tracking: 'Activity Tracking: Logging keystrokes, mouse movements, active window focus, and app or website usage.' (two markers, unresolved tokens)", "T1-4 visual monitoring: 'Visual Monitoring: Taking periodic or continuous screenshots and recording webcams.' (two markers, unresolved tokens)", "T1-5 location and biometrics: 'Location & Biometrics: Tracking real-time GPS locations, facial recognition, or physical movement metrics.' (two markers: an unresolved token and card 1's)", "T1-6 productivity scoring: 'Productivity Scoring: Generating automated daily scores or flagged alerts for \"productive\" versus \"unproductive\" behavior.' (two markers: card 3's token and an unresolved token)", "T1-7 the database as current: 'The Coworker Worktech Database tracks a wide range of platforms across categories' (inline link and one marker, card 1's token)", "T1-8 monitoring examples: 'Productivity & Monitoring Software: ActivTrak, Hubstaff, Time Doctor, Desklog, and Controlio.' (three markers: card 1's, card 2's and an unresolved token)", "T1-9 industry examples: 'Industry-Specific & Logistics Tracking: Amazon internal tools (such as Project Ultraviolet, Mentor App, and WiFi Tracking), Alice Housekeeping (hotel worker tracking), and Netradyne (fleet/driver monitoring).' (one marker, card 1's token)", "T1-10 hiring examples: 'Hiring & AI Analytics: HireVue (voice and interview analysis), Arctic Shores (behavioral hiring assessments), and Arya (AI recruiting).' (two markers: card 1's and card 3's tokens)", "T1-11 privacy: 'Research highlighted by institutions like Vanderbilt Law School shows that many workplace monitoring apps collect deep data profiles (including personal emails, device data, and location records) and share them with third-party tech and advertising domains.' (inline link and one marker, card 2's token)", "T1-12 closer: 'Would you like to search for information on specific monitoring tools, state disclosure laws, or how to audit what software is running on a device?'" ], "markers": "Inline links and citation markers are google.com/goto tokens. Three resolve by the inline links that carry them: the link on the database's name and on 'Coworker Worktech Database' is card 1's token (CAESWwHr…), the link on 'Vanderbilt Law School' card 2's (CAESlAEB…), and the Facebook card's video link card 3's (CAESxwEB…). Card 1's token marks T1-1, T1-5 [2], T1-7, T1-8 [1], T1-9 and T1-10 [1]; card 2's marks T1-8 [2] and T1-11; card 3's marks T1-6 [1] and T1-10 [2]. Five tokens (CAESiQEB…, CAESaAHr…, CAESYgHrOzAVFtGF…, CAESYgHrOzAVUHYE…, CAESaQHr…) are the five other cards' in some order and cannot be resolved. The paste is the Overview expanded (operator's default of 2026-10-01; the 'AI Mode Conversation' view is the expanded Overview, operator 2026-10-18); signed out, incognito (operator's default of 2026-10-14). One turn.", "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/T1-bossware-and-employment-tech-database-aio-20261029.txt" } ] }, "KO": { "title": "Bossware and Employment Tech Database", "genre": "knowledge object, equal case, under EA-NEGONT-02 v0.9 (#1690): the archive's sources and the field's admitted on equal terms, ontology included, in one claim space", "status": "composed 2026-10-29 under v0.9 (briefs rebuild/negative-of-the-negative/v09/BRIEF-NEW-ROW-AGGREGATOR.md, BRIEF-NEW-ROW-PROVENANCE.md and BRIEF-NEW-ROW-LABOR.md); not frozen; ledgers unaudited", "sentences": [ { "n": 1, "para": 0, "sense": "what it is", "text": "The Bossware and Employment Tech Database is a database (Labor Vector census record) of which its operator writes, \"Coworker.org’s Bossware and Employment Tech database compiles more than 550 labor-focused technology products that are changing our relationship to work\" (Coworker, database page), counted by the census as 635 product rows in the page saved on 2026-10-29 (census record), and its report gives the same products as \"assembled into a searchable database and dubbed Little Tech\" (the report).", "claims": [ "LV-01", "F1", "LV-12", "F2" ] }, { "n": 2, "para": 0, "sense": "what it is", "text": "The page is dated 17 November 2021 (Coworker, database page); the research ran from November 2020 to May 2021 and catalogued products, \"not the companies that created\" them, 31% of which emerged between 2020 and 2021 and the rest between 2018 and 2020 (the report), the period the census records (census record).", "claims": [ "F3", "F4", "F5", "LV-11" ] }, { "n": 3, "para": 1, "sense": "scope", "text": "Its operator places it in a trend, \"Since 2018 we’ve seen a rise in the use of tech to manage the world’s labor force\", and gives its scope as companies, \"and their products and investors\", that \"touch every part of the labor process, from hiring to productivity monitoring and more\", products \"that use technology like AI, location tracking, and biometrics to manage employees and collect their data — often without their knowledge\", the table being there to \"learn more about the companies behind this emerging trend\" (Coworker, database page).", "claims": [ "F6", "F12", "F13", "F14" ] }, { "n": 4, "para": 1, "sense": "who supplies, directs, gains", "text": "The census reads it first under AI governing labor, \"hiring, surveillance, scheduling, quotas, evaluation and discipline\", then under the distribution of gains and losses and under worker power (census record), and puts to it its organizing question, \"Who supplies the labor, who directs it, and who receives its gains\" (census record).", "claims": [ "LV-02", "LV-31", "LV-30" ] }, { "n": 5, "para": 1, "sense": "who supplies, directs, gains", "text": "The record answers from the table itself: the labor is supplied by the workers each product targets, hourly, contract, salaried, non-management and management, the report centring low-wage and hourly workers; it is directed by \"employers who buy and deploy the products\", through the vendors who make them; and the gains go to the vendors and investors each row names (census record), while the report states that the products are contributing to the reduction of labor standards, continuing to shift the costs of production onto workers, and fissuring labor markets (the report).", "claims": [ "LV-06", "LV-05", "LV-07", "LV-08", "F26" ] }, { "n": 6, "para": 2, "sense": "the table", "text": "Its unit is one table row per product, with the parent company, category, type, targeted workers, investors and assessments of its data practices against worker-rights criteria, and its evidence is of two kinds, a product inventory and a rating against standards (census record).", "claims": [ "LV-04", "LV-03" ] }, { "n": 7, "para": 2, "sense": "the table", "text": "The report sorts the products into four areas, performance and productivity monitoring, safety, benefits, health and well-being, and labor, job market and workplace optimization, and finds most of them promoting workplace safety (40%) or optimizing the functioning of labor markets (38%) (the report).", "claims": [ "F15", "F16" ] }, { "n": 8, "para": 2, "sense": "the table", "text": "The census's tally of the saved table gives 242 rows in Labor Market Optimization, 178 in performance and productivity monitoring, 176 in safety, 34 in benefits and 5 in two categories, 595 products in use and 206 emerged during Covid-19, and it records as unchecked that the report's 40% and 38% are not reproduced by the table and whether the rows include products added after the report (census record); the table opens row by row on the page (Coworker, database page), with the report as a PDF download (census record).", "claims": [ "LV-13", "LV-28", "LV-29", "F20", "LV-19" ] }, { "n": 9, "para": 2, "sense": "the assessment", "text": "Each row assesses the product's own terms against worker-rights criteria, among them \"Informed consent obtained\", whether the worker can access, interpret and correct their own data, a grievance mechanism, forced use of the tool, discrimination potential and the right to freedom of association (Coworker, database page), an analysis the report says had to move \"beyond a privacy-only framework\", and on privacy itself it finds that \"Only 35% of the products share any information on privacy policy and data sharing arrangements\" (the report).", "claims": [ "F21", "F22", "F24", "F23" ] }, { "n": 10, "para": 3, "sense": "the report and Little Tech", "text": "The accompanying report, Little Tech Is Coming for Workers: A Framework for Reclaiming and Building Worker Power, by Wilneida Negrón, PhD, \"analyzes the ways they’re harming workers, labor standards, and the economy\" (Coworker, database page); it is © 2021 Coworker.org under CC BY-NC-ND 4.0 (the report), the licence the census records for the report alone, none being stated for the table (census record).", "claims": [ "F7", "F8", "F10", "LV-20" ] }, { "n": 11, "para": 3, "sense": "the report and Little Tech", "text": "The report names the marketplace the database catalogues Little Tech, the unregulated marketplace of tech products, companies and investors collecting and aggregating data about workers at almost every step of the labor process, and credits the database's research and making to Ayden Federline (the report).", "claims": [ "F9", "F11" ] }, { "n": 12, "para": 3, "sense": "findings", "text": "Its first finding is that \"The current proliferation of tech products has the potential to continue eroding labor standards and weaken worker voice and worker power, while also increasing the potential for discrimination and other harms\", among the ways it names the accelerating commodification of low-wage workers' data (the report).", "claims": [ "F25", "F27" ] }, { "n": 13, "para": 3, "sense": "findings", "text": "It finds a historic amount of private capital behind the products' proliferation and low-wage workers navigating \"scientifically questionable\" hiring and background check technologies, and its conclusion explores the implications of more than 550 products that appeared in the workplace and job markets during the pandemic (the report).", "claims": [ "F28", "F29", "F30" ] }, { "n": 14, "para": 4, "sense": "hiring as production", "text": "Hiring is in the table as products: the HireVue row, \"HireVue AI Facial Recognition\", under Labor Market Optimization, describes video interviews and AI-driven pre-hire assessments in which job seekers' behavior, intonation and speech are fed to an algorithm that assigns traits, and records the product as Discontinued (Coworker, database page).", "claims": [ "F17", "F18" ] }, { "n": 15, "para": 4, "sense": "hiring as production", "text": "Of that class the archive's measure of uncompensated applicant labor applies, by its own statement of scope, to technical hiring platforms and \"AI interview firms\" (#747), and AI interview platforms, \"Firms like HireVue, Karat, and emerging AI-mediated interview operators\", collect video, audio, response timing and behavioral data from candidates at scale, data that is institutional capital while \"The candidates' labor is supplied free\" (#747).", "claims": [ "O747-01", "O747-03" ] }, { "n": 16, "para": 4, "sense": "hiring as production", "text": "What a screening apparatus produces, on #747's definition, is calibration intelligence, durable knowledge derived from aggregate applicant interaction and \"the operator's principal source of competitive advantage\"; technical-hiring platforms capture calibration data while candidates pay in unpaid preparation labor, and rejected applicants become the training set of the next cycle's apparatus (#747).", "claims": [ "O747-02", "O747-04", "O747-05" ] }, { "n": 17, "para": 4, "sense": "hiring as production", "text": "#747 states its own limit, alleging no individual design, no illegality and no uniquely culpable party, \"Structural extraction does not require an extractor\", and asks only \"that the relation be named correctly\" (#747).", "claims": [ "O747-06", "O747-07" ] }, { "n": 18, "para": 5, "sense": "limits", "text": "The report states that the database \"is not exhaustive\", hundreds more emerging products and non-U.S. products having been omitted or overlooked, and that collection stopped once the researchers felt they had sufficient evidence of Little Tech's pervasiveness; built at the product level, it omits smaller Big Tech companies, Uber, Lyft and DoorDash among them (the report).", "claims": [ "F31", "F32" ] }, { "n": 19, "para": 5, "sense": "limits", "text": "Its method is desk research on public documents, investors from Crunchbase, app permissions from the Google Play store and privacy from public privacy statements, terms of service and impact assessments (the report; census record); the report primarily discusses low-wage and hourly workers, and holds that workers' own reports would show how the technologies are implemented in the workplace beyond the products' stated uses and business goals (the report).", "claims": [ "F33", "LV-09", "F35", "F34" ] }, { "n": 20, "para": 5, "sense": "limits", "text": "The census carries the limits as its coverage, 42 origin territories with 461 of 635 rows from the United States, non-U.S. products omitted or overlooked, as a stated limit, and as two negative tags, \"NOT an exhaustive census of workplace technology\" and \"NOT a record of the Big Tech gig platforms, which it omits\" (census record).", "claims": [ "LV-10", "LV-14", "LV-24", "LV-26" ] }, { "n": 21, "para": 5, "sense": "what it is not", "text": "Its lifecycle is historical, with no later update stated on the saved page, and the census tags it \"NOT a measure of how widely any product is deployed\" and \"NOT updated since 2021 on the saved page\"; its evidence can settle which workplace technology products existed in 2020 to 2021 and what their public documents say about consent, access to data, grievance, data sharing and law-enforcement access, and cannot settle how any product is used at a workplace or how often, its effect on wages, workload or employment, or products after May 2021 (census record).", "claims": [ "LV-21", "LV-22", "LV-25", "LV-15", "LV-16" ] }, { "n": 22, "para": 5, "sense": "what it is not", "text": "The page invites workers to share their stories (Coworker, database page), and the report holds that listing, classifying and analyzing Little Tech's direct harms can build worker voice and power and strengthen regulation (the report); the census tags the database \"NOT worker testimony\", the table holding none (census record).", "claims": [ "F36", "F37", "LV-23" ] }, { "n": 23, "para": 6, "sense": "where it meets Labor Vector", "text": "In the archive's reading the database \"inventories the products through which employers direct work and collect workers' data, product by product\" and \"meets the directionality stack at the layer of who directs labor\"; it records nothing on whether a system's labor advanced a commissioned task, \"so DSL and task-origin find no measurement in it\" (census record).", "claims": [ "LV-17", "LV-18" ] }, { "n": 24, "para": 7, "sense": "operator and neighbour", "text": "Its operator is Coworker.org, \"a global platform to advance change in the workplace\" (Coworker, database page); the report compares its data points with the \"UC Berkeley Labor Center’s list in their report\" (the report), and the census makes Negotiating Tech its neighbour (census record).", "claims": [ "F38", "F39", "LV-27" ] }, { "n": 25, "para": 8, "sense": "the term", "text": "Bossware, the word in its name, is given in the press as \"technology and AI tools used by managers to supervise, surveil, and track employee habits, output, and biometrics\" (New York Times, snippet only), and in video titles as watching people while they work (Bloomberg Originals), as \"70% of U.S. Employers Track Workers\" (Ronan Farrow on Facebook, title only, no source given), as a thing to break into \"for Fun and Ethics\" (media.ccc.de), and as questions, \"What’s the Deal with Bossware?\" (Kyla Scanlon) and \"Is your boss watching you right now?\" (PDQ).", "claims": [ "F40", "F41", "F42", "F43", "F44", "F45" ] }, { "n": 26, "para": 8, "sense": "another study", "text": "A separate study, by researchers at Northeastern's Khoury College, the Vanderbilt Policy Accelerator, UC Berkeley's Center for Consumer Law and Economic Justice and Columbia's Center for Law and the Economy, reported on 27 May 2026, signed up as an employer to nine workplace monitoring platforms, Apploye, Deputy, Desklog, Hubstaff, Monitask, Buddy Punch, Time Doctor 2, Vericlock and When I Work, and logged in as an employee (Vanderbilt Law School).", "claims": [ "F49", "F47", "F48", "F50" ] }, { "n": 27, "para": 8, "sense": "another study", "text": "It found the platforms \"systematically sharing personal data about workers and online activity with hundreds of outside data brokers and big tech companies\": all nine shared identifying worker data, in 121 instances, online activity went to 145 third-party domains, and a third can track workers' precise location at any time; its authors find current protections insufficient and recommend banning the sale or sharing of worker data, and Ganesh Sitaraman holds that workers \"likely have no idea\" their data is collected and distributed (Vanderbilt Law School).", "claims": [ "F46", "F51", "F52", "F53", "F55", "F54" ] }, { "n": 28, "para": 9, "sense": "the composition at the name", "text": "At its own name on Google's AI Overview, 2026-10-29, the composition identified the database and its size, explained the term, gave examples from the database and added a recent study: \"more than 550\" is the database's own count and every product named appears in the saved table, checked against the census record and its saved sources; it named the operator and cited its page, no person and no identifier, at PER 0.5, and called it \"Coworker Worktech Database\", a variant from the URL slug (Capture Registry, 2026-10-29).", "claims": [ "CAP-1-09", "CAP-1-01", "CAP-1-02", "CAP-1-13", "CAP-1-12" ] }, { "n": 29, "para": 9, "sense": "the composition at the name", "text": "The registry finds the record's lifecycle historical and the composition in the present tense with no date, \"A 2021 inventory is composed as a live catalogue\", and the record's negative tags, not a measure of deployment and not updated since 2021, \"are what a reader would need to use its examples\" (Capture Registry, 2026-10-29); two of the products it named, Amazon's warehouse WiFi tracking and HireVue's AI facial recognition, are Discontinued in the table (Coworker, database page).", "claims": [ "CAP-1-03", "CAP-1-04", "CAP-1-07", "CAP-1-08", "F18", "F19" ] }, { "n": 30, "para": 9, "sense": "the composition at the name", "text": "It finds the database's own limits and its 35% privacy finding not composed, its purpose and its investors absent, and the privacy paragraph to be another study's finding, that of Vanderbilt Law School's card, which the record keeps outside the database (Capture Registry, 2026-10-29); no card cites the census record, which landed the same day (Capture Registry, 2026-10-29), and Wikipedia has no article on the database or on Coworker.org (Wikipedia, 2026-10-29).", "claims": [ "CAP-1-05", "CAP-1-11", "CAP-1-06", "CAP-1-10", "F56" ] } ], "joins": [ { "act": "order of senses", "sentences": "1–30", "claims": [], "note": "equal case (§4.7): the entity's dependency order, field and archive claims ordered together by genealogy within each sense; neither ledger placed first as a block. What it is (¶0) precedes its scope and the census's question of who supplies, directs and gains (¶1), which the table answers (¶2); the report and its findings (¶3) follow the table they analyse; hiring (¶4) stands where the table's own HireVue row places it, the archive's reading of the class beside it; the limits and what the evidence is not (¶5) qualify everything before; where it meets Labor Vector (¶6), the operator and the neighbour (¶7), the term and another study that the field holds (¶8), and the composition at the name (¶9) stand last, as relations and receptions of the entity already composed." }, { "act": "holding together (direction and its costs)", "sentences": [ 5 ], "claims": [ "LV-06", "LV-07", "LV-08", "F26" ], "note": "the census's answer to who supplies, directs and gains, composed beside the report's statement that costs are shifted onto workers, which the census itself cites as the basis of its 'gains' field (evidence 'costs'): one lineage, the report keeping the date" }, { "act": "holding apart (the report's percentages and the table's counts)", "sentences": [ 7, 8 ], "claims": [ "F16", "LV-13", "LV-28" ], "note": "P_coh: the report's 40% safety and 38% labor-market optimisation against the census's tally of the saved table (176 and 242 of 635 rows), which the census records as unchecked; each with its source; open block" }, { "act": "holding beside (hiring: the table's row and the archive's class)", "sentences": [ 14, 15, 16, 17 ], "claims": [ "F17", "F18", "O747-01", "O747-02", "O747-03", "O747-04", "O747-05", "O747-06", "O747-07" ], "note": "the class (hiring, recruitment and screening technology) is sourced by B1's scope and category and B9's taxonomy, stated in the configuration before the pass (§3.4 O guard); #747's categories are composed as bearing on the class, HireVue named in both, and not on the database, which #747 does not name" }, { "act": "holding apart (another study)", "sentences": [ 26, 27 ], "claims": [ "F46", "F47", "F48", "F49", "F50", "F51", "F52", "F53", "F54", "F55" ], "note": "the Northeastern–Vanderbilt–Berkeley–Columbia investigation of nine monitoring platforms is a distinct entity on the same class, composed as such; it does not name the database" }, { "act": "placing the composition after the limits", "sentences": [ 28, 29, 30 ], "claims": [ "CAP-1-03", "CAP-1-04", "CAP-1-05", "CAP-1-07", "CAP-1-08", "CAP-1-11", "CAP-1-06" ], "note": "the registry's account of the composition at the name stands after the limits, the lifecycle and the other study, so that 'given as current' and 'its own limits unsaid' are read against F3–F5, F31–F35 and LV-21–LV-26 as composed" } ], "plan": { "order": [ "LV-01", "F1", "LV-12", "F2", "F3", "F4", "F5", "LV-11", "F6", "F12", "F13", "F14", "LV-02", "LV-31", "LV-30", "LV-06", "LV-05", "LV-07", "LV-08", "F26", "LV-04", "LV-03", "F15", "F16", "LV-13", "LV-28", "LV-29", "F20", "LV-19", "F21", "F22", "F24", "F23", "F7", "F8", "F10", "LV-20", "F9", "F11", "F25", "F27", "F28", "F29", "F30", "F17", "F18", "O747-01", "O747-03", "O747-02", "O747-04", "O747-05", "O747-06", "O747-07", "F31", "F32", "F33", "LV-09", "F35", "F34", "LV-10", "LV-14", "LV-24", "LV-26", "LV-21", "LV-22", "LV-25", "LV-15", "LV-16", "F36", "F37", "LV-23", "LV-17", "LV-18", "F38", "F39", "LV-27", "F40", "F41", "F42", "F43", "F44", "F45", "F49", "F47", "F48", "F50", "F46", "F51", "F52", "F53", "F55", "F54", "CAP-1-09", "CAP-1-01", "CAP-1-02", "CAP-1-13", "CAP-1-12", "CAP-1-03", "CAP-1-04", "CAP-1-07", "CAP-1-08", "F19", "CAP-1-05", "CAP-1-11", "CAP-1-06", "CAP-1-10", "F56" ], "senses": { "what it is": [ 1, 2 ], "scope": [ 3 ], "who supplies, directs, gains": [ 4, 5 ], "the table": [ 6, 7, 8 ], "the assessment": [ 9 ], "the report and Little Tech": [ 10, 11 ], "findings": [ 12, 13 ], "hiring as production": [ 14, 15, 16, 17 ], "limits": [ 18, 19, 20 ], "what it is not": [ 21, 22 ], "where it meets Labor Vector": [ 23 ], "operator and neighbour": [ 24 ], "the term": [ 25 ], "another study": [ 26, 27 ], "the composition at the name": [ 28, 29, 30 ] }, "case_by_sense": { "equal (one claim space; nothing translated)": [ "what it is", "scope", "who supplies, directs, gains", "the table", "the assessment", "the report and Little Tech", "findings", "hiring as production", "limits", "what it is not", "where it meets Labor Vector", "operator and neighbour", "the term", "another study", "the composition at the name" ] }, "carried": { "archive": 51, "field": 56, "not_composed": {} }, "conflict_log": [ { "rule": "D_pres vs channel", "result": "no cut: the KO carries every field and archive claim; the compression's bound met with no channel log" }, { "rule": "P_coh", "result": "F16 (40% and 38%) against LV-13/LV-28 (the table's 176 and 242 of 635) (sentences 7–8): each composed with its source" }, { "rule": "N_c", "result": "no claim lowered by standing; self-descriptions carried at their grade (F31, F32, F34, F35, F38; LV-14, LV-28, LV-29); the archive's reading (LV-17, LV-18) and #747's interpretations at interpretation grade; #747's limits (O747-06, O747-07) carried because it states them; F42's figure carried as its title states it, with 'no source given'" }, { "rule": "O_leg", "result": "no opaque material in the ledgers" }, { "rule": "C_ex", "result": "senses composed ⊇ senses in the ledgers: every ledger lineage cited in the KO" } ] } }, "P": { "title": "Bossware and Employment Tech Database", "genre": "the compression: AIO's interaction grammar (lede, headed clusters, bolded labels, card rail), composed from the v0.9 plan in one claim space; it faces on the card", "status": "composed 2026-10-29 from the v0.9 knowledge object; not frozen", "lede": { "text": "is Coworker.org's database of more than 550 labor-focused technology products, researched 2020 to 2021 and published 17 November 2021, that touch the labor process from hiring to productivity monitoring, each assessed against worker-rights criteria (Coworker; the report; census record); it is historical and not exhaustive (census record; the report).", "claims": [ "F1", "LV-01", "LV-12", "F3", "F4", "F12", "F13", "F21", "LV-21", "F31" ] }, "sections": [ { "icon": "🗂️", "head": "What it holds", "items": [ { "label": "Products:", "text": "one row each, 635 saved; monitoring, safety, benefits, labor-market optimization (census record; the report).", "claims": [ "LV-04", "LV-03", "LV-13", "F15", "F16", "LV-28", "LV-29", "F20", "LV-19", "F2", "LV-11", "F5" ] }, { "label": "Scope:", "text": "AI, location tracking and biometrics, \"often without their knowledge\" (Coworker).", "claims": [ "F6", "F12", "F13", "F14" ] }, { "label": "Assessment:", "text": "consent, workers' access to their data, grievance, forced use; only 35% share privacy information (Coworker; the report).", "claims": [ "F21", "F22", "F24", "F23" ] } ] }, { "icon": "⚖️", "head": "Who supplies, directs, gains", "items": [ { "label": "Supplies:", "text": "the workers each product targets, low-wage and hourly workers at the report's centre (census record).", "claims": [ "LV-30", "LV-02", "LV-31", "LV-06", "LV-05" ] }, { "label": "Directs:", "text": "employers who deploy the products, through vendors (census record).", "claims": [ "LV-07" ] }, { "label": "Gains:", "text": "vendors and investors; costs shifted onto workers (census record; the report).", "claims": [ "LV-08", "F26" ] } ] }, { "icon": "📕", "head": "The report", "items": [ { "label": "Little Tech:", "text": "an unregulated marketplace aggregating data about workers (Negrón, 2021; CC BY-NC-ND).", "claims": [ "F7", "F8", "F9", "F10", "F11", "LV-20" ] }, { "label": "Findings:", "text": "eroding labor standards and worker power; capital-driven; questionable hiring tech (the report).", "claims": [ "F25", "F27", "F28", "F29", "F30" ] } ] }, { "icon": "🧭", "head": "Hiring as production", "items": [ { "label": "Screening:", "text": "AI interview platforms such as HireVue, in the table, capture candidates' data as institutional capital, the labor supplied free; no illegality alleged (#747).", "claims": [ "F17", "F18", "O747-01", "O747-02", "O747-03", "O747-04", "O747-05", "O747-06", "O747-07" ] } ] }, { "icon": "⚠️", "head": "Limits", "items": [ { "label": "Not exhaustive:", "text": "non-U.S. and emerging products, and the gig platforms, omitted (the report; census record).", "claims": [ "F31", "F32", "LV-10", "LV-14", "LV-24", "LV-26" ] }, { "label": "Public documents:", "text": "use, frequency and effect on wages it cannot show (the report; census record).", "claims": [ "F33", "LV-09", "F34", "F35", "LV-15", "LV-16", "LV-22" ] }, { "label": "Not current:", "text": "no update since 2021 (census record).", "claims": [ "LV-21", "LV-25" ] }, { "label": "Not testimony:", "text": "stories invited, none held (Coworker; census record).", "claims": [ "F36", "F37", "LV-23" ] } ] }, { "icon": "🔗", "head": "Labor Vector", "items": [ { "label": "Direction:", "text": "the layer of who directs labor; no DSL or task-origin measurement (census record).", "claims": [ "LV-17", "LV-18" ] }, { "label": "Operator:", "text": "Coworker.org; neighbour Negotiating Tech (Coworker; the report; census record).", "claims": [ "F38", "F39", "LV-27" ] } ] }, { "icon": "📝", "head": "Record and composition", "items": [ { "label": "Bossware:", "text": "managers' tools to supervise, surveil and track (New York Times, snippet; video titles).", "claims": [ "F40", "F41", "F42", "F43", "F44", "F45" ] }, { "label": "Another study:", "text": "nine monitoring platforms shared worker data, 2026 (Vanderbilt Law School).", "claims": [ "F46", "F47", "F48", "F49", "F50", "F51", "F52", "F53", "F54", "F55" ] }, { "label": "At the name:", "text": "count and products held; given as current, limits unsaid, another study's privacy finding beside it (Capture Registry, 2026-10-29).", "claims": [ "CAP-1-09", "CAP-1-01", "CAP-1-02", "CAP-1-13", "CAP-1-12", "CAP-1-03", "CAP-1-04", "CAP-1-07", "CAP-1-08", "CAP-1-05", "CAP-1-11", "CAP-1-06", "F19" ] }, { "label": "Reception:", "text": "no card cites the record; no Wikipedia article (Capture Registry; Wikipedia).", "claims": [ "CAP-1-10", "F56" ] } ] } ], "open": [ { "question": "Is the inventory current?", "rests_on": [ "F3", "F4", "LV-21", "LV-25", "LV-29", "F18", "F19", "CAP-1-04" ], "modality": "documented (page, report, table), stipulation (census tags), self-description (census unchecked), documented (Capture Registry)", "would_resolve": "a dated update of the page or the table, or a status for each listed product after May 2021" }, { "question": "The report's 40% and 38%, or the table's 176 and 242 of 635?", "rests_on": [ "F16", "LV-13", "LV-28" ], "modality": "documented (the report), documented (census tally), self-description (census unchecked)", "would_resolve": "the report's counting rule, or the table as it stood on 17 November 2021" }, { "question": "How are the products used, how often, and with what effect on wages and work?", "rests_on": [ "LV-16", "LV-22", "F34", "F36", "LV-23" ], "modality": "interpretation and stipulation (census record), self-description (the report), documented (the page)", "would_resolve": "worker testimony or workplace observation of a listed product, which the database does not hold" }, { "question": "Does the hiring technology the table lists produce calibration intelligence from applicants' unpaid labor, as #747 holds of the class?", "rests_on": [ "O747-01", "O747-02", "O747-03", "F17", "F18" ], "modality": "stipulation and interpretation (#747), documented (the table)", "would_resolve": "funnel-shape and data-retention evidence from a listed hiring product; #747 alleges no illegality and asks only that the relation be named (O747-06, O747-07)" }, { "question": "What do the five cards not reached say?", "rests_on": [ "F40", "F41", "F42", "F43", "F45" ], "modality": "stipulation (the New York Times snippet), documented and interpretation (titles only)", "would_resolve": "the New York Times article at its own URL; the Facebook post; the three videos' transcripts (two refused by bot check, two not found)" } ], "rail": [ { "lineage": "what it is: Coworker.org's database of more than 550 labor-focused technology products", "claims": [ "LV-01", "F1", "LV-12", "F2" ], "earliest": "B1" }, { "lineage": "publication and the research period", "claims": [ "F3", "F4", "F5", "LV-11", "LV-21" ], "earliest": "B1" }, { "lineage": "scope: the whole labor process, products and investors; AI, location tracking and biometrics", "claims": [ "F6", "F12", "F13", "F14" ], "earliest": "B1" }, { "lineage": "the census's question: who supplies the labor, who directs it, who gains", "claims": [ "LV-02", "LV-31", "LV-30", "LV-06", "LV-05", "LV-07", "LV-08", "LV-03" ], "earliest": "LV" }, { "lineage": "findings: labor standards, worker voice and power, costs shifted onto workers", "claims": [ "F26", "F25", "F27", "F28", "F29", "F30" ], "earliest": "B9" }, { "lineage": "the assessment of each product's data practices against worker-rights criteria", "claims": [ "LV-04", "F21", "F22", "F24", "F23" ], "earliest": "B1" }, { "lineage": "the table: categories, products and their status", "claims": [ "F15", "F16", "LV-13", "LV-28", "LV-29", "F20", "LV-19", "F17", "F18", "F19" ], "earliest": "B1" }, { "lineage": "the accompanying report and its name for the marketplace, Little Tech", "claims": [ "F7", "F8", "F10", "LV-20", "F9", "F11" ], "earliest": "B1" }, { "lineage": "the archive's category on the class: hiring and screening as production", "claims": [ "O747-01", "O747-03", "O747-02", "O747-04", "O747-05", "O747-06", "O747-07" ], "earliest": 747 }, { "lineage": "stated limits: not exhaustive, product level, public documents", "claims": [ "F31", "F32", "F33", "LV-09", "F35", "F34", "LV-10", "LV-14", "LV-24", "LV-26" ], "earliest": "B9" }, { "lineage": "what it is not", "claims": [ "LV-22", "LV-25" ], "earliest": "LV" }, { "lineage": "what this evidence can and cannot settle", "claims": [ "LV-15", "LV-16" ], "earliest": "LV" }, { "lineage": "workers' stories and what they would supply", "claims": [ "F36", "F37", "LV-23" ], "earliest": "B1" }, { "lineage": "where it meets Labor Vector's instruments", "claims": [ "LV-17", "LV-18" ], "earliest": "LV" }, { "lineage": "the operator: Coworker.org", "claims": [ "F38" ], "earliest": "B1" }, { "lineage": "neighbour: the UC Berkeley Labor Center's list", "claims": [ "F39", "LV-27" ], "earliest": "B9" }, { "lineage": "the term bossware, in press and video", "claims": [ "F40", "F41", "F42", "F43", "F44", "F45" ], "earliest": "B5" }, { "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "claims": [ "F49", "F47", "F48", "F50", "F46", "F51", "F52", "F53", "F55", "F54" ], "earliest": "B2" }, { "lineage": "the composition at the name: what it held", "claims": [ "CAP-1-09", "CAP-1-01", "CAP-1-02", "CAP-1-13", "CAP-1-12" ], "earliest": "CAP" }, { "lineage": "the composition at the name: a 2021 inventory given as current", "claims": [ "CAP-1-03", "CAP-1-04", "CAP-1-07", "CAP-1-08" ], "earliest": "CAP" }, { "lineage": "the composition at the name: the database's limits unsaid", "claims": [ "CAP-1-05", "CAP-1-11" ], "earliest": "CAP" }, { "lineage": "the composition at the name: another study's finding beside the database", "claims": [ "CAP-1-06" ], "earliest": "CAP" }, { "lineage": "reception: the record and the cards", "claims": [ "CAP-1-10" ], "earliest": "CAP" }, { "lineage": "reception: the encyclopedia", "claims": [ "F56" ], "earliest": "B10" } ], "body_words": 315, "entity": "Composed under v0.9, equal case (ρ = extends): KO_B sentences surviving 0 of 12; every field claim carried." }, "P_B": { "title": "Bossware and Employment Tech Database", "arm": "B (the field alone)", "genre": "popup — the compression from the field ledger alone (cards, own page, Wikipedia)", "status": "composed 2026-10-29 from the field ledger alone; not frozen", "lede": { "text": "is Coworker.org's database of more than 550 labor-focused technology products, published 17 November 2021 with its report, Little Tech Is Coming for Workers (Coworker; the report).", "claims": [ "F1", "F3", "F7", "F2" ] }, "sections": [ { "icon": "🗂️", "head": "What it holds", "items": [ { "label": "Products:", "text": "AI, location tracking, biometrics, from hiring to monitoring; four areas (Coworker; the report).", "claims": [ "F4", "F5", "F6", "F12", "F13", "F14", "F15", "F16", "F17", "F18", "F19", "F20" ] }, { "label": "Assessment:", "text": "consent, data access, grievance; only 35% share privacy information (Coworker; the report).", "claims": [ "F21", "F22", "F23", "F24" ] } ] }, { "icon": "📕", "head": "The report", "items": [ { "label": "Findings:", "text": "labor standards eroded, costs shifted onto workers (the report).", "claims": [ "F8", "F9", "F10", "F11", "F25", "F26", "F27", "F28", "F29", "F30" ] }, { "label": "Limits:", "text": "not exhaustive; product level; public documents (the report).", "claims": [ "F31", "F32", "F33", "F34", "F35" ] } ] }, { "icon": "📝", "head": "Around it", "items": [ { "label": "Operator:", "text": "Coworker.org; stories invited (Coworker; the report).", "claims": [ "F36", "F37", "F38", "F39" ] }, { "label": "Bossware:", "text": "managers' tools to track employees (New York Times; titles).", "claims": [ "F40", "F41", "F42", "F43", "F44", "F45" ] }, { "label": "Another study:", "text": "nine monitoring platforms shared worker data (Vanderbilt Law School).", "claims": [ "F46", "F47", "F48", "F49", "F50", "F51", "F52", "F53", "F54", "F55" ] }, { "label": "Wikipedia:", "text": "no article.", "claims": [ "F56" ] } ] } ], "open": [ { "question": "40% and 38%, against the table?", "rests_on": [ "F16" ], "modality": "documented", "would_resolve": "the report's counting rule" }, { "question": "How are the products used?", "rests_on": [ "F34", "F36" ], "modality": "self-description, documented", "would_resolve": "workers' reports" } ], "rail": [ { "lineage": "what it is: Coworker.org's database of more than 550 labor-focused technology products", "claims": [ "F1", "F2" ], "earliest": "B1" }, { "lineage": "publication and the research period", "claims": [ "F3", "F4", "F5" ], "earliest": "B1" }, { "lineage": "scope: the whole labor process, products and investors; AI, location tracking and biometrics", "claims": [ "F6", "F12", "F13", "F14" ], "earliest": "B1" }, { "lineage": "the table: categories, products and their status", "claims": [ "F15", "F16", "F20", "F17", "F18", "F19" ], "earliest": "B1" }, { "lineage": "the assessment of each product's data practices against worker-rights criteria", "claims": [ "F21", "F22", "F24", "F23" ], "earliest": "B1" }, { "lineage": "the accompanying report and its name for the marketplace, Little Tech", "claims": [ "F7", "F8", "F9", "F10", "F11" ], "earliest": "B1" }, { "lineage": "findings: labor standards, worker voice and power, costs shifted onto workers", "claims": [ "F25", "F26", "F27", "F28", "F29", "F30" ], "earliest": "B9" }, { "lineage": "stated limits: not exhaustive, product level, public documents", "claims": [ "F31", "F32", "F33", "F34", "F35" ], "earliest": "B9" }, { "lineage": "workers' stories and what they would supply", "claims": [ "F36", "F37" ], "earliest": "B1" }, { "lineage": "the operator: Coworker.org", "claims": [ "F38" ], "earliest": "B1" }, { "lineage": "neighbour: the UC Berkeley Labor Center's list", "claims": [ "F39" ], "earliest": "B9" }, { "lineage": "the term bossware, in press and video", "claims": [ "F40", "F41", "F42", "F43", "F44", "F45" ], "earliest": "B5" }, { "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "claims": [ "F47", "F48", "F49", "F50", "F46", "F51", "F52", "F53", "F54", "F55" ], "earliest": "B2" }, { "lineage": "reception: the encyclopedia", "claims": [ "F56" ], "earliest": "B10" } ], "body_words": 105, "entity": "With no archive claim admitted, the entry is Coworker's database at its own pages' resolution: its products, its assessment, its report and limits, the term in its name and another study of the class." }, "KO_B": { "title": "Bossware and Employment Tech Database", "arm": "B (the field alone)", "genre": "knowledge object", "status": "composed 2026-10-29; not frozen", "sentences": [ { "n": 1, "para": 0, "text": "Coworker.org's database is given by its operator as compiling \"more than 550 labor-focused technology products that are changing our relationship to work\", on a page dated 17 November 2021 (Coworker), and by its report as more than 550 products in a searchable database dubbed Little Tech, researched November 2020 to May 2021, 31% of them emerging in 2020 to 2021 (the report).", "claims": [ "F1", "F3", "F2", "F4", "F5" ] }, { "n": 2, "para": 0, "text": "It covers companies, their products and investors, across the labor process from hiring to productivity monitoring, products using AI, location tracking and biometrics to manage employees and collect their data, often without their knowledge, in a trend of technology managing labor since 2018 (Coworker).", "claims": [ "F6", "F12", "F13", "F14" ] }, { "n": 3, "para": 1, "text": "The report sorts the products into four areas and finds most promoting safety (40%) or labor-market optimization (38%); the table opens row by row, among its rows HireVue's AI facial recognition and Amazon's warehouse WiFi tracking, both Discontinued (the report; Coworker).", "claims": [ "F15", "F16", "F20", "F17", "F18", "F19" ] }, { "n": 4, "para": 1, "text": "Each product is assessed on informed consent, workers' access to and correction of their data, grievance, forced use, discrimination and association, beyond a privacy-only framework, and only 35% share any privacy information (Coworker; the report).", "claims": [ "F21", "F22", "F24", "F23" ] }, { "n": 5, "para": 2, "text": "The accompanying report, Little Tech Is Coming for Workers, by Wilneida Negrón, PhD, © 2021 Coworker.org under CC BY-NC-ND 4.0, defines Little Tech as an unregulated marketplace collecting data about workers at almost every step of the labor process and credits the database to Ayden Federline (Coworker; the report).", "claims": [ "F7", "F8", "F9", "F10", "F11" ] }, { "n": 6, "para": 2, "text": "It finds the products eroding labor standards and worker voice and power, shifting costs onto workers and commodifying workers' data, driven by private capital, with questionable hiring technologies, across more than 550 products of the pandemic (the report).", "claims": [ "F25", "F26", "F27", "F28", "F29", "F30" ] }, { "n": 7, "para": 3, "text": "Its limits: not exhaustive, collection stopped once pervasiveness was evident, smaller Big Tech platforms omitted at the product level, public documents its method, low-wage workers its focus, and workers' reports needed for how the products are actually used (the report).", "claims": [ "F31", "F32", "F33", "F34", "F35" ] }, { "n": 8, "para": 3, "text": "The page invites workers' stories, the report holds that listing harms builds worker power, the operator calls itself a platform to advance change in the workplace, and the report compares its data points with the UC Berkeley Labor Center's list (Coworker; the report).", "claims": [ "F36", "F37", "F38", "F39" ] }, { "n": 9, "para": 4, "text": "Bossware is defined in the press as managers' technology and AI tools to supervise, surveil and track employees (New York Times, snippet), and video titles give it as watching workers, as tracked by 70% of U.S. employers, as a thing to break into, and as a question (titles only).", "claims": [ "F40", "F41", "F42", "F43", "F44", "F45" ] }, { "n": 10, "para": 5, "text": "A 2026 study by Northeastern, Vanderbilt, Berkeley and Columbia researchers, posing as an employer, examined nine workplace monitoring platforms (Vanderbilt Law School).", "claims": [ "F47", "F48", "F49", "F50" ] }, { "n": 11, "para": 5, "text": "It found all nine sharing identifying worker data with third parties and online activity with 145 domains, a third able to track location at any time, and recommends banning the sale or sharing of worker data (Vanderbilt Law School).", "claims": [ "F46", "F51", "F52", "F53", "F54", "F55" ] }, { "n": 12, "para": 6, "text": "Wikipedia has no article on the database or its operator (Wikipedia, 2026-10-29).", "claims": [ "F56" ] } ] }, "L_B": { "words": 478, "text": "Coworker.org's database is given by its operator as compiling \"more than 550 labor-focused technology products that are changing our relationship to work\", on a page dated 17 November 2021 (Coworker), and by its report as more than 550 products in a searchable database dubbed Little Tech, researched November 2020 to May 2021, 31% of them emerging in 2020 to 2021 (the report). It covers companies, their products and investors, across the labor process from hiring to productivity monitoring, products using AI, location tracking and biometrics to manage employees and collect their data, often without their knowledge, in a trend of technology managing labor since 2018 (Coworker). The report sorts the products into four areas and finds most promoting safety (40%) or labor-market optimization (38%); the table opens row by row, among its rows HireVue's AI facial recognition and Amazon's warehouse WiFi tracking, both Discontinued (the report; Coworker). Each product is assessed on informed consent, workers' access to and correction of their data, grievance, forced use, discrimination and association, beyond a privacy-only framework, and only 35% share any privacy information (Coworker; the report). The accompanying report, Little Tech Is Coming for Workers, by Wilneida Negrón, PhD, © 2021 Coworker.org under CC BY-NC-ND 4.0, defines Little Tech as an unregulated marketplace collecting data about workers at almost every step of the labor process and credits the database to Ayden Federline (Coworker; the report). It finds the products eroding labor standards and worker voice and power, shifting costs onto workers and commodifying workers' data, driven by private capital, with questionable hiring technologies, across more than 550 products of the pandemic (the report). Its limits: not exhaustive, collection stopped once pervasiveness was evident, smaller Big Tech platforms omitted at the product level, public documents its method, low-wage workers its focus, and workers' reports needed for how the products are actually used (the report). The page invites workers' stories, the report holds that listing harms builds worker power, the operator calls itself a platform to advance change in the workplace, and the report compares its data points with the UC Berkeley Labor Center's list (Coworker; the report). Bossware is defined in the press as managers' technology and AI tools to supervise, surveil and track employees (New York Times, snippet), and video titles give it as watching workers, as tracked by 70% of U.S. employers, as a thing to break into, and as a question (titles only). A 2026 study by Northeastern, Vanderbilt, Berkeley and Columbia researchers, posing as an employer, examined nine workplace monitoring platforms (Vanderbilt Law School). It found all nine sharing identifying worker data with third parties and online activity with 145 domains, a third able to track location at any time, and recommends banning the sale or sharing of worker data (Vanderbilt Law School). Wikipedia has no article on the database or its operator (Wikipedia, 2026-10-29).", "note": "L_F(B), the field composed in the field's ontology (v0.9 §0.4), realized as objects.KO_B; its rail is P_B's, by lineage." }, "L_BA": { "words": 1935, "text": "The Bossware and Employment Tech Database is a database (Labor Vector census record) of which its operator writes, \"Coworker.org’s Bossware and Employment Tech database compiles more than 550 labor-focused technology products that are changing our relationship to work\" (Coworker, database page), counted by the census as 635 product rows in the page saved on 2026-10-29 (census record), and its report gives the same products as \"assembled into a searchable database and dubbed Little Tech\" (the report). The page is dated 17 November 2021 (Coworker, database page); the research ran from November 2020 to May 2021 and catalogued products, \"not the companies that created\" them, 31% of which emerged between 2020 and 2021 and the rest between 2018 and 2020 (the report), the period the census records (census record). Its operator places it in a trend, \"Since 2018 we’ve seen a rise in the use of tech to manage the world’s labor force\", and gives its scope as companies, \"and their products and investors\", that \"touch every part of the labor process, from hiring to productivity monitoring and more\", products \"that use technology like AI, location tracking, and biometrics to manage employees and collect their data — often without their knowledge\", the table being there to \"learn more about the companies behind this emerging trend\" (Coworker, database page). The census reads it first under AI governing labor, \"hiring, surveillance, scheduling, quotas, evaluation and discipline\", then under the distribution of gains and losses and under worker power (census record), and puts to it its organizing question, \"Who supplies the labor, who directs it, and who receives its gains\" (census record). The record answers from the table itself: the labor is supplied by the workers each product targets, hourly, contract, salaried, non-management and management, the report centring low-wage and hourly workers; it is directed by \"employers who buy and deploy the products\", through the vendors who make them; and the gains go to the vendors and investors each row names (census record), while the report states that the products are contributing to the reduction of labor standards, continuing to shift the costs of production onto workers, and fissuring labor markets (the report). Its unit is one table row per product, with the parent company, category, type, targeted workers, investors and assessments of its data practices against worker-rights criteria, and its evidence is of two kinds, a product inventory and a rating against standards (census record). The report sorts the products into four areas, performance and productivity monitoring, safety, benefits, health and well-being, and labor, job market and workplace optimization, and finds most of them promoting workplace safety (40%) or optimizing the functioning of labor markets (38%) (the report). The census's tally of the saved table gives 242 rows in Labor Market Optimization, 178 in performance and productivity monitoring, 176 in safety, 34 in benefits and 5 in two categories, 595 products in use and 206 emerged during Covid-19, and it records as unchecked that the report's 40% and 38% are not reproduced by the table and whether the rows include products added after the report (census record); the table opens row by row on the page (Coworker, database page), with the report as a PDF download (census record). Each row assesses the product's own terms against worker-rights criteria, among them \"Informed consent obtained\", whether the worker can access, interpret and correct their own data, a grievance mechanism, forced use of the tool, discrimination potential and the right to freedom of association (Coworker, database page), an analysis the report says had to move \"beyond a privacy-only framework\", and on privacy itself it finds that \"Only 35% of the products share any information on privacy policy and data sharing arrangements\" (the report). The accompanying report, Little Tech Is Coming for Workers: A Framework for Reclaiming and Building Worker Power, by Wilneida Negrón, PhD, \"analyzes the ways they’re harming workers, labor standards, and the economy\" (Coworker, database page); it is © 2021 Coworker.org under CC BY-NC-ND 4.0 (the report), the licence the census records for the report alone, none being stated for the table (census record). The report names the marketplace the database catalogues Little Tech, the unregulated marketplace of tech products, companies and investors collecting and aggregating data about workers at almost every step of the labor process, and credits the database's research and making to Ayden Federline (the report). Its first finding is that \"The current proliferation of tech products has the potential to continue eroding labor standards and weaken worker voice and worker power, while also increasing the potential for discrimination and other harms\", among the ways it names the accelerating commodification of low-wage workers' data (the report). It finds a historic amount of private capital behind the products' proliferation and low-wage workers navigating \"scientifically questionable\" hiring and background check technologies, and its conclusion explores the implications of more than 550 products that appeared in the workplace and job markets during the pandemic (the report). Hiring is in the table as products: the HireVue row, \"HireVue AI Facial Recognition\", under Labor Market Optimization, describes video interviews and AI-driven pre-hire assessments in which job seekers' behavior, intonation and speech are fed to an algorithm that assigns traits, and records the product as Discontinued (Coworker, database page). Of that class the archive's measure of uncompensated applicant labor applies, by its own statement of scope, to technical hiring platforms and \"AI interview firms\" (#747), and AI interview platforms, \"Firms like HireVue, Karat, and emerging AI-mediated interview operators\", collect video, audio, response timing and behavioral data from candidates at scale, data that is institutional capital while \"The candidates' labor is supplied free\" (#747). What a screening apparatus produces, on #747's definition, is calibration intelligence, durable knowledge derived from aggregate applicant interaction and \"the operator's principal source of competitive advantage\"; technical-hiring platforms capture calibration data while candidates pay in unpaid preparation labor, and rejected applicants become the training set of the next cycle's apparatus (#747). #747 states its own limit, alleging no individual design, no illegality and no uniquely culpable party, \"Structural extraction does not require an extractor\", and asks only \"that the relation be named correctly\" (#747). The report states that the database \"is not exhaustive\", hundreds more emerging products and non-U.S. products having been omitted or overlooked, and that collection stopped once the researchers felt they had sufficient evidence of Little Tech's pervasiveness; built at the product level, it omits smaller Big Tech companies, Uber, Lyft and DoorDash among them (the report). Its method is desk research on public documents, investors from Crunchbase, app permissions from the Google Play store and privacy from public privacy statements, terms of service and impact assessments (the report; census record); the report primarily discusses low-wage and hourly workers, and holds that workers' own reports would show how the technologies are implemented in the workplace beyond the products' stated uses and business goals (the report). The census carries the limits as its coverage, 42 origin territories with 461 of 635 rows from the United States, non-U.S. products omitted or overlooked, as a stated limit, and as two negative tags, \"NOT an exhaustive census of workplace technology\" and \"NOT a record of the Big Tech gig platforms, which it omits\" (census record). Its lifecycle is historical, with no later update stated on the saved page, and the census tags it \"NOT a measure of how widely any product is deployed\" and \"NOT updated since 2021 on the saved page\"; its evidence can settle which workplace technology products existed in 2020 to 2021 and what their public documents say about consent, access to data, grievance, data sharing and law-enforcement access, and cannot settle how any product is used at a workplace or how often, its effect on wages, workload or employment, or products after May 2021 (census record). The page invites workers to share their stories (Coworker, database page), and the report holds that listing, classifying and analyzing Little Tech's direct harms can build worker voice and power and strengthen regulation (the report); the census tags the database \"NOT worker testimony\", the table holding none (census record). In the archive's reading the database \"inventories the products through which employers direct work and collect workers' data, product by product\" and \"meets the directionality stack at the layer of who directs labor\"; it records nothing on whether a system's labor advanced a commissioned task, \"so DSL and task-origin find no measurement in it\" (census record). Its operator is Coworker.org, \"a global platform to advance change in the workplace\" (Coworker, database page); the report compares its data points with the \"UC Berkeley Labor Center’s list in their report\" (the report), and the census makes Negotiating Tech its neighbour (census record). Bossware, the word in its name, is given in the press as \"technology and AI tools used by managers to supervise, surveil, and track employee habits, output, and biometrics\" (New York Times, snippet only), and in video titles as watching people while they work (Bloomberg Originals), as \"70% of U.S. Employers Track Workers\" (Ronan Farrow on Facebook, title only, no source given), as a thing to break into \"for Fun and Ethics\" (media.ccc.de), and as questions, \"What’s the Deal with Bossware?\" (Kyla Scanlon) and \"Is your boss watching you right now?\" (PDQ). A separate study, by researchers at Northeastern's Khoury College, the Vanderbilt Policy Accelerator, UC Berkeley's Center for Consumer Law and Economic Justice and Columbia's Center for Law and the Economy, reported on 27 May 2026, signed up as an employer to nine workplace monitoring platforms, Apploye, Deputy, Desklog, Hubstaff, Monitask, Buddy Punch, Time Doctor 2, Vericlock and When I Work, and logged in as an employee (Vanderbilt Law School). It found the platforms \"systematically sharing personal data about workers and online activity with hundreds of outside data brokers and big tech companies\": all nine shared identifying worker data, in 121 instances, online activity went to 145 third-party domains, and a third can track workers' precise location at any time; its authors find current protections insufficient and recommend banning the sale or sharing of worker data, and Ganesh Sitaraman holds that workers \"likely have no idea\" their data is collected and distributed (Vanderbilt Law School). At its own name on Google's AI Overview, 2026-10-29, the composition identified the database and its size, explained the term, gave examples from the database and added a recent study: \"more than 550\" is the database's own count and every product named appears in the saved table, checked against the census record and its saved sources; it named the operator and cited its page, no person and no identifier, at PER 0.5, and called it \"Coworker Worktech Database\", a variant from the URL slug (Capture Registry, 2026-10-29). The registry finds the record's lifecycle historical and the composition in the present tense with no date, \"A 2021 inventory is composed as a live catalogue\", and the record's negative tags, not a measure of deployment and not updated since 2021, \"are what a reader would need to use its examples\" (Capture Registry, 2026-10-29); two of the products it named, Amazon's warehouse WiFi tracking and HireVue's AI facial recognition, are Discontinued in the table (Coworker, database page). It finds the database's own limits and its 35% privacy finding not composed, its purpose and its investors absent, and the privacy paragraph to be another study's finding, that of Vanderbilt Law School's card, which the record keeps outside the database (Capture Registry, 2026-10-29); no card cites the census record, which landed the same day (Capture Registry, 2026-10-29), and Wikipedia has no article on the database or on Coworker.org (Wikipedia, 2026-10-29).", "rail": [], "note": "L(B ∪ A) in the equal-terms case (v0.9 §0.4), realized as the knowledge object (objects.KO); its rail is the compression's, by lineage." } }, "field": [ { "id": "B1", "card": "home.coworker.org — Bossware and Employment Tech Database - Coworker", "fetched": "card; fetched 2026-10-29T22:35:44Z HTTP 200; B1.html sha256 3da111faf8c8f673; text B1.txt; the census's saved copy agrees in text (B1-census.*)", "origin": "card" }, { "id": "B2", "card": "Vanderbilt Law School — Bossware Is Spying on Workers and Sharing Their Data | Vanderbilt Law School | Vanderbilt University", "fetched": "card; fetched 2026-10-29T22:35:45Z HTTP 200; B2.html sha256 3e09c1c0b94ffd8c; text B2.txt", "origin": "card" }, { "id": "B3", "card": "Facebook·Ronan Farrow — Bossware Workplace Surveillance: 70% of U.S. Employers Track Workers", "fetched": "unreachable: URL not found (2 searches); card title only", "origin": "card" }, { "id": "B4", "card": "YouTube·media.ccc.de — Pwning Bossware for Fun and Ethics", "fetched": "unreachable: https://www.youtube.com/watch?v=YonqzeD5HA0 HTTP 429; card title only", "origin": "card" }, { "id": "B5", "card": "The New York Times — Are ‘Bossware’ Tools Tracking You? 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the unregulat- … ed marketplace of tech products that are col- … lecting and aggregating data about workers at … almost every step of the labor process", "claim": "Little Tech defined: the unregulated marketplace of tech products, companies and investors collecting and aggregating data about workers at almost every step of the labor process", "modality": "stipulation", "kind": "definition", "kernel": true, "const": true, "lineage": "the accompanying report and its name for the marketplace, Little Tech", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F10": { "source": "B9", "origin": "own_page", "locus": "p. 3, colophon", "quote": "Little Tech Is Coming for Workers: A Framework for Reclaiming and Building Worker Power, © 2021 by Coworker.org, is licensed under Attribution NonCommercial-NoDerivatives 4.0 International.", "claim": "the report is © 2021 Coworker.org under CC BY-NC-ND 4.0", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "the accompanying report and its name for the marketplace, Little Tech", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F11": { "source": "B9", "origin": "own_page", "locus": "p. 3, Acknowledgements ¶2", "quote": "An extra special shoutout to Ayden Federline for meticulously and graciously researching and creating the database of employment tech products.", "claim": "the database was researched and created by Ayden Federline", "modality": "documented", "kind": "attribution", "kernel": false, "const": false, "lineage": "the accompanying report and its name for the marketplace, Little Tech", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F12": { "source": "B1", "origin": "card", "locus": "header, ¶4 s1", "quote": "In the database you’ll find companies — and their products and investors — that touch every part of the labor process, from hiring to productivity monitoring and more.", "claim": "scope: companies, their products and investors, touching every part of the labor process from hiring to productivity monitoring", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "scope: the whole labor process, products and investors; AI, location tracking and biometrics", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F13": { "source": "B1", "origin": "card", "locus": "header, ¶4 s2", "quote": "Organized by category, type, and date founded, the database covers products that use technology like AI, location tracking, and biometrics to manage employees and collect their data — often without their knowledge.", "claim": "the database covers products that use AI, location tracking and biometrics to manage employees and collect their data, often without their knowledge", "modality": "stipulation", "kind": "definition", "kernel": true, "const": true, "lineage": "scope: the whole labor process, products and investors; AI, location tracking and biometrics", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F14": { "source": "B1", "origin": "card", "locus": "header, ¶5", "quote": "Use the table and the filters below to learn more about the companies behind this emerging trend:", "claim": "purpose: to learn about the companies behind the trend", "modality": "stipulation", "kind": "function", "kernel": false, "const": false, "lineage": "scope: the whole labor process, products and investors; AI, location tracking and biometrics", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F15": { "source": "B9", "origin": "own_page", "locus": "The Scope of the Study, p. 24, the four areas", "quote": "1. Workplace performance, productivity monitoring 2. Workplace safety 3. Workplace benefits, health, and well-being 4. Labor, job market, and workplace optimization", "claim": "the products are categorized in four areas: performance and productivity monitoring; safety; benefits, health and well-being; labor, job market and workplace optimization", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "the table: categories, products and their status", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F16": { "source": "B9", "origin": "own_page", "locus": "The Scope of the Study, p. 26, left column ¶1", "quote": "Based on this taxonomy, we found that most … products are either trying to promote work- … place safety (40%) or optimize the functioning … of the labor markets (38%).", "claim": "most products promote workplace safety (40%) or optimize the functioning of labor markets (38%)", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "the table: categories, products and their status", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F17": { "source": "B1", "origin": "card", "locus": "table, row 'HireVue AI Facial Recognition' (Product Name through Type)", "quote": "HireVue AI Facial Recognition HireVue, Inc https://www.hirevue.com/ HireVue's Hiring Intelligence Platform claims to deliver the best talent, faster, with video interviews and AI-driven pre-hire assessments No Labor Market Optimization App or Software", "claim": "the table's HireVue row: HireVue AI Facial Recognition, video interviews and AI-driven pre-hire assessments, category Labor Market Optimization", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "the table: categories, products and their status", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F18": { "source": "B1", "origin": "card", "locus": "table, row 'HireVue AI Facial Recognition' (Current Business Goals, end, and Status)", "quote": "Their behavior, intonation, and speech is fed to an algorithm that assigns certain traits and qualities Discontinued", "claim": "the HireVue row: job seekers' behavior, intonation and speech fed to an algorithm that assigns traits; status Discontinued", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "the table: categories, products and their status", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F19": { "source": "B1", "origin": "card", "locus": "table, row 'Amazon.com - Fulfilment Center WiFi Tracking' (Product Name through Status)", "quote": "Amazon.com - Fulfilment Center WiFi Tracking Amazon.com Inc https://www.amazon.com/ Amazon is an international e-commerce website for consumers, sellers, and content creators Yes Workplace Safety Hardware Hourly, non-management * Gives Amazon a way to track workers’ locations inside warehouses so they can develop better social distancing and cleanliness plans Discontinued", "claim": "the table's Amazon WiFi Tracking row: emerged during Covid-19, Workplace Safety, hardware tracking workers' locations in warehouses for social distancing; status Discontinued", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "the table: categories, products and their status", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F20": { "source": "B1", "origin": "card", "locus": "table header and instruction", "quote": "Click the \"+\" next to the product name to expand the table.", "claim": "data access: a table expanded row by row on the page", "modality": "documented", "kind": "function", "kernel": false, "const": false, "lineage": "the table: categories, products and their status", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F21": { "source": "B1", "origin": "card", "locus": "table header, columns 30–32", "quote": "Informed consent obtained Can the worker access and interpret their own data? Can the worker correct incorrect data?", "claim": "each product is assessed on informed consent and on whether the worker can access, interpret and correct their data", "modality": "stipulation", "kind": "definition", "kernel": true, "const": false, "lineage": "the assessment of each product's data practices against worker-rights criteria", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F22": { "source": "B1", "origin": "card", "locus": "table header, columns 37–40", "quote": "Grievance mechanism Forced use of tool Discrimination potential Right to freedom of association", "claim": "each product is assessed on grievance mechanism, forced use, discrimination potential and freedom of association", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "the assessment of each product's data practices against worker-rights criteria", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F23": { "source": "B9", "origin": "own_page", "locus": "Economic Drivers and Political Context, p. 33, left column", "quote": "Only 35% of the products share any information on privacy policy and data sharing arrangements.", "claim": "only 35% of the products share any information on privacy policy and data sharing arrangements", "modality": "documented", "kind": "fact", "kernel": true, "const": false, "lineage": "the assessment of each product's data practices against worker-rights criteria", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F24": { "source": "B9", "origin": "own_page", "locus": "The Scope of the Study, p. 26, left column ¶3", "quote": "Central to our analysis was needing to move … beyond a privacy-only framework and begin", "claim": "the analysis moves beyond a privacy-only framework to the risks each product poses to workers", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "the assessment of each product's data practices against worker-rights criteria", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F25": { "source": "B9", "origin": "own_page", "locus": "Executive Summary, finding 1 (heading)", "quote": "1. The current proliferation of tech products has the potential to continue eroding labor standards and weaken worker voice and worker power, while also increasing the potential for discrimination and other harms.", "claim": "finding 1: the proliferation of these products has the potential to keep eroding labor standards and weakening worker voice and power, and raises the potential for discrimination and other harms", "modality": "interpretation", "kind": "interpretation", "kernel": true, "const": false, "lineage": "findings: labor standards, worker voice and power, costs shifted onto workers", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F26": { "source": "B9", "origin": "own_page", "locus": "Executive Summary, finding 1, left column bullet 1", "quote": "they are contributing to the ongoing … reduction of labor standards,5 continu- … ing to shift the costs of production onto … workers6, and fissuring labor markets.7", "claim": "the products contribute to the reduction of labor standards, continue to shift the costs of production onto workers, and fissure labor markets", "modality": "interpretation", "kind": "interpretation", "kernel": false, "const": false, "lineage": "findings: labor standards, worker voice and power, costs shifted onto workers", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F27": { "source": "B9", "origin": "own_page", "locus": "Executive Summary, finding 1, right column bullet 3", "quote": "Accelerating the commodification of … low-wage workers’ data, particularly", "claim": "the products accelerate the commodification of low-wage workers' data", "modality": "interpretation", "kind": "interpretation", "kernel": false, "const": false, "lineage": "findings: labor standards, worker voice and power, costs shifted onto workers", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F28": { "source": "B9", "origin": "own_page", "locus": "Executive Summary, finding 2 (heading)", "quote": "2. A historic amount of private capital is contributing to the proliferation of tech products to be used in the workplace and in the labor markets.", "claim": "finding 2: a historic amount of private capital drives the proliferation of these products", "modality": "interpretation", "kind": "interpretation", "kernel": false, "const": false, "lineage": "findings: labor standards, worker voice and power, costs shifted onto workers", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F29": { "source": "B9", "origin": "own_page", "locus": "Table of Contents, p. 67 entry", "quote": "Low-wage workers must navigate scientifically questionable hiring … and background check technologies.", "claim": "low-wage workers must navigate scientifically questionable hiring and background check technologies", "modality": "interpretation", "kind": "interpretation", "kernel": false, "const": false, "lineage": "findings: labor standards, worker voice and power, costs shifted onto workers", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F30": { "source": "B9", "origin": "own_page", "locus": "Conclusion, left column ¶1 s1–2", "quote": "This report explores the implications of more … than 550 technology products that have … appeared in the workplace and job markets … during the pandemic.", "claim": "the report explores the implications of more than 550 products that appeared in the workplace and job markets during the pandemic", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "findings: labor standards, worker voice and power, costs shifted onto workers", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F31": { "source": "B9", "origin": "own_page", "locus": "The Scope of the Study, left column ¶2", "quote": "note that the database is not exhaustive, … and we omitted or overlooked hundreds … more products that were still emerging or in … development as well as non-U.S. products. … We stopped collecting information once … we felt we had sufficient evidence of the … pervasiveness of Little Tech as well as a", "claim": "the database is not exhaustive: hundreds of emerging or in-development products and non-U.S. products were omitted or overlooked, and collection stopped once there was sufficient evidence of pervasiveness", "modality": "self-description", "kind": "fact", "kernel": true, "const": false, "lineage": "stated limits: not exhaustive, product level, public documents", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F32": { "source": "B9", "origin": "own_page", "locus": "Executive Summary, footnote 2", "quote": "Please note that we do omit from this analysis smaller Big Tech companies, such as Twitter, Airbnb, Uber, Lyft, DoorDash, InstaCart, GrubHub, Care.com, and Handy, as we developed the database at the product and not company level, and we were looking at products that had emerged in the workplace in the past one to two years.", "claim": "the database omits smaller Big Tech companies (Twitter, Airbnb, Uber, Lyft, DoorDash and others), being built at the product level and on products of the past one to two years", "modality": "self-description", "kind": "fact", "kernel": false, "const": false, "lineage": "stated limits: not exhaustive, product level, public documents", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F33": { "source": "B9", "origin": "own_page", "locus": "footnote 66", "quote": "Investor information was obtained from Crunchbase. For app permissions and hardware usage data, we have relied on the data available in the Google Play store for Android devices. In assessing the privacy implications of a product, we have relied on publicly accessible privacy statements, terms of service documents, and public impact assessments.", "claim": "method: investors from Crunchbase, app permissions from the Google Play store, privacy from public privacy statements, terms of service and impact assessments", "modality": "stipulation", "kind": "definition", "kernel": false, "const": false, "lineage": "stated limits: not exhaustive, product level, public documents", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F34": { "source": "B9", "origin": "own_page", "locus": "Executive Summary, finding 5, right column ¶1", "quote": "context for how these technologies are actu- … ally implemented in the workplace (rather than … relying on the products’ stated use/purposes … and business goals).", "claim": "workers' reports would give context on how the technologies are actually implemented, beyond the products' stated uses and business goals", "modality": "self-description", "kind": "interpretation", "kernel": false, "const": false, "lineage": "stated limits: not exhaustive, product level, public documents", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F35": { "source": "B9", "origin": "own_page", "locus": "The Scope of the Study, left column ¶1 s2", "quote": "report primarily discusses the experience of … low-wage and hourly workers, because these", "claim": "the report primarily discusses low-wage and hourly workers", "modality": "self-description", "kind": "fact", "kernel": false, "const": false, "lineage": "stated limits: not exhaustive, product level, public documents", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F36": { "source": "B1", "origin": "card", "locus": "header, worker invitation", "quote": "are you a worker who interacts with any of the tech in our database? … Click here to share your story with our team .", "claim": "workers who interact with the database's technology are invited to share their stories", "modality": "documented", "kind": "function", "kernel": false, "const": false, "lineage": "workers' stories and what they would supply", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F37": { "source": "B9", "origin": "own_page", "locus": "Executive Summary, finding 5 (heading)", "quote": "5. Listing, classifying, and analyzing Little Tech’s direct harms can build worker voice and power and strengthen regulatory efforts.", "claim": "finding 5: listing, classifying and analyzing Little Tech's direct harms can build worker voice and power and strengthen regulation", "modality": "interpretation", "kind": "interpretation", "kernel": false, "const": false, "lineage": "workers' stories and what they would supply", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F38": { "source": "B1", "origin": "card", "locus": "footer, the operator's statement", "quote": "Coworker.org is a global platform to advance change in the workplace.", "claim": "the operator: Coworker.org, a global platform to advance change in the workplace", "modality": "self-description", "kind": "attribution", "kernel": false, "const": false, "lineage": "the operator: Coworker.org", "date": "2021-11-17 (the page's date)", "quote_ok": true, "checked_against": "saved text B1.txt (sha256 d65bf2a5da233188…), whitespace-normalised" }, "F39": { "source": "B9", "origin": "own_page", "locus": "The Scope of the Study, p. 26, left column ¶2", "quote": "UC Berkeley Labor Center’s list in their report", "claim": "the data points collected match those on the UC Berkeley Labor Center's list", "modality": "attributed", "kind": "genealogy", "kernel": false, "const": false, "lineage": "neighbour: the UC Berkeley Labor Center's list", "date": "2021 (the report, © 2021; published with the database 2021-11-17)", "quote_ok": true, "checked_against": "saved text B9-pdf.txt (sha256 d44621da795a48b7…), whitespace-normalised" }, "F40": { "source": "B5", "origin": "card", "locus": "card title and snippet", "quote": "Definition: \"Bossware\" refers to technology and AI tools used by managers to supervise, surveil, and track employee habits, output, and biometrics across indust...", "claim": "bossware defined: technology and AI tools managers use to supervise, surveil and track employee habits, output and biometrics", "modality": "stipulation", "kind": "definition", "kernel": true, "const": false, "lineage": "the term bossware, in press and video", "date": "undated (snippet only)", "quote_ok": true, "checked_against": "the card's title and snippet (cite_list n=5, data/EA-WG-CAPTURES-01.json)" }, "F41": { "source": "B6", "origin": "card", "locus": "card title", "quote": "How Bossware is Watching While You Work", "claim": "bossware watches people while they work (a video's title)", "modality": "interpretation", "kind": "interpretation", "kernel": true, "const": false, "lineage": "the term bossware, in press and video", "date": "undated (title only)", "quote_ok": true, "checked_against": "the card's title and snippet (cite_list n=6, data/EA-WG-CAPTURES-01.json)" }, "F42": { "source": "B3", "origin": "card", "locus": "card title", "quote": "Bossware Workplace Surveillance: 70% of U.S. Employers Track Workers", "claim": "70% of U.S. employers track workers (a video post's title; no source given)", "modality": "documented", "kind": "fact", "kernel": true, "const": false, "lineage": "the term bossware, in press and video", "date": "undated (title only)", "quote_ok": true, "checked_against": "the card's title and snippet (cite_list n=3, data/EA-WG-CAPTURES-01.json)", "note": "the figure's source is not on the card; the post was not reached" }, "F43": { "source": "B4", "origin": "card", "locus": "card title", "quote": "Pwning Bossware for Fun and Ethics", "claim": "a talk on breaking into bossware, for fun and ethics", "modality": "documented", "kind": "fact", "kernel": true, "const": false, "lineage": "the term bossware, in press and video", "date": "undated (title only)", "quote_ok": true, "checked_against": "the card's title and snippet (cite_list n=4, data/EA-WG-CAPTURES-01.json)" }, "F44": { "source": "B7", "origin": "card", "locus": "card title (and the page's script data)", "quote": "What’s the Deal with Bossware?", "claim": "a short explainer asking what bossware is", "modality": "documented", "kind": "fact", "kernel": true, "const": false, "lineage": "the term bossware, in press and video", "date": "about 2026-06 (the page's '4 months ago' on 2026-10-29)", "quote_ok": true, "checked_against": "the card's title (cite_list n=7) and B7.html's script data" }, "F45": { "source": "B8", "origin": "card", "locus": "card title", "quote": "Is your boss watching you right now? 👁️ #bossware #privacy #worklife", "claim": "a short video asking whether the viewer's boss is watching", "modality": "documented", "kind": "fact", "kernel": true, "const": false, "lineage": "the term bossware, in press and video", "date": "undated (title only)", "quote_ok": true, "checked_against": "the card's title and snippet (cite_list n=8, data/EA-WG-CAPTURES-01.json)" }, "F46": { "source": "B2", "origin": "card", "locus": "¶1 s1", "quote": "A new investigation finds that workplace monitoring platforms are systematically sharing personal data about workers and online activity with hundreds of outside data brokers and big tech companies in ways that are not clearly disclosed and that, in some cases, may contradict the platforms’ own privacy policies.", "claim": "an investigation finds workplace monitoring platforms systematically sharing workers' personal data and online activity with hundreds of outside data brokers and big tech companies, not clearly disclosed", "modality": "documented", "kind": "fact", "kernel": true, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F47": { "source": "B2", "origin": "card", "locus": "dateline", "quote": "May 27, 2026, 12:47 PM", "claim": "the post is dated 27 May 2026", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F48": { "source": "B2", "origin": "card", "locus": "¶1 s2", "quote": "The researchers examined nine widely used workplace monitoring platforms — Apploye, Deputy, Desklog, Hubstaff, Monitask, Buddy Punch, Time Doctor 2, Vericlock, and When I Work, tracking how each app collects and shares worker data in practice.", "claim": "the sample: nine workplace monitoring platforms, Apploye, Deputy, Desklog, Hubstaff, Monitask, Buddy Punch, Time Doctor 2, Vericlock and When I Work", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F49": { "source": "B2", "origin": "card", "locus": "¶2 s1", "quote": "The report was authored by researchers at the Khoury College of Computer and Information Sciences at Northeastern University; the Vanderbilt Policy Accelerator at Vanderbilt University; the Center for Consumer Law and Economic Justice at UC Berkeley Law School; and the Center for Law and the Economy at Columbia Law School.", "claim": "the study's authors are at Northeastern's Khoury College, the Vanderbilt Policy Accelerator, UC Berkeley's Center for Consumer Law and Economic Justice and Columbia's Center for Law and the Economy", "modality": "documented", "kind": "attribution", "kernel": false, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F50": { "source": "B2", "origin": "card", "locus": "What Researchers Found, ¶1", "quote": "by signing up as an employer, setting up bossware services for workers, then logging in as an employee.", "claim": "method: the researchers signed up as an employer, set up the services for workers and logged in as an employee", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F51": { "source": "B2", "origin": "card", "locus": "What Researchers Found, 'Worker data shared'", "quote": "All (9 of 9) workplace monitoring platforms directly shared identifying worker data including first name, last name, email, and company to third parties. … The researchers recorded 121 unique instances of worker data being shared with companies including Facebook, Google, Microsoft, and AppLovin (a mobile advertising platform).", "claim": "all nine platforms shared identifying worker data (first name, last name, email, company) with third parties, 121 unique instances", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F52": { "source": "B2", "origin": "card", "locus": "What Researchers Found, 'Online activity shared'", "quote": "The 9 workplace monitoring platforms in the sample shared information about workers’ online activities (such as IP address, device information, web pages visited, unique identifiers, etc.) to a total of 145 unique third-party domains", "claim": "the nine platforms shared workers' online activity to 145 third-party domains", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F53": { "source": "B2", "origin": "card", "locus": "What Researchers Found, 'Location tracking'", "quote": "One third of the workplace monitoring platforms in the sample have features that track workers’ precise location at any time – even when the app is in the background or potentially when the worker is clocked out.", "claim": "a third of the platforms can track workers' precise location at any time, even in the background or potentially when clocked out", "modality": "documented", "kind": "fact", "kernel": false, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F54": { "source": "B2", "origin": "card", "locus": "¶ quotation, Sitaraman", "quote": "“‘Bossware’ is increasingly common in jobs of all kinds, and workers likely have no idea that their data is being systemically collected and distributed to unknown data brokers and tech companies,” said Ganesh Sitaraman, Director at Vanderbilt Policy Accelerator.", "claim": "Sitaraman: bossware is increasingly common, and workers likely do not know their data is collected and distributed", "modality": "attributed", "kind": "interpretation", "kernel": false, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F55": { "source": "B2", "origin": "card", "locus": "A Call for Urgent Policy Action, ¶1", "quote": "The report argues that protections currently in place to protect workers from employee surveillance, including sharing of their workplace data, are insufficient. … Key recommendations include banning the sale or sharing of worker data, prohibiting unlimited data retention, and barring collection of sensitive employee information.", "claim": "the study finds protections insufficient and recommends banning the sale or sharing of worker data, unlimited retention and collection of sensitive information", "modality": "interpretation", "kind": "interpretation", "kernel": false, "const": false, "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "date": "2026-05-27 (the post)", "quote_ok": true, "checked_against": "saved text B2.txt (sha256 5785a927a4f74558…), whitespace-normalised" }, "F56": { "source": "B10", "origin": "wikipedia", "locus": "Wikipedia: title Bossware_and_Employment_Tech_Database; title Coworker.org; article-space searches", "quote": "raw wikitext, title Bossware_and_Employment_Tech_Database (action=raw, redirect=no), 2026-10-29T22:38:52Z: HTTP 404 … Wikipedia does not have an article with this exact name. … raw wikitext, title Coworker.org (the operator; action=raw, redirect=no), 2026-10-29T22:39:03Z: HTTP 404 … There were no results matching the query.", "claim": "Wikipedia has no article on the database or on Coworker.org, no redirect, and no article text naming the database, its report, or Coworker.org with bossware", "modality": "documented", "kind": "fact", "kernel": true, "const": false, "lineage": "reception: the encyclopedia", "date": "2026-10-29 (as fetched)", "quote_ok": true, "checked_against": "saved text B10.txt (sha256 5ce02788a98b2a5d…), whitespace-normalised" } }, "field_sources": { "B1": "home.coworker.org — Bossware and Employment Tech Database - Coworker", "B2": "Vanderbilt Law School — Bossware Is Spying on Workers and Sharing Their Data | Vanderbilt Law School | Vanderbilt University", "B3": "Facebook·Ronan Farrow — Bossware Workplace Surveillance: 70% of U.S. Employers Track Workers", "B4": "YouTube·media.ccc.de — Pwning Bossware for Fun and Ethics", "B5": "The New York Times — Are ‘Bossware’ Tools Tracking You? - The New York Times", "B6": "YouTube·Bloomberg Originals — How Bossware is Watching While You Work", "B7": "YouTube·Kyla Scanlon — What's the Deal with Bossware?", "B8": "YouTube·PDQ — Is your boss watching you right now? 👁️ #bossware #privacy #worklife", "B9": "home.coworker.org — Little Tech Is Coming for Workers: A Framework for Reclaiming and Building Worker Power (PDF, 73 pages)", "B10": "Wikipedia — Bossware and Employment Tech Database (no article)" }, "delta": { "T_vs_LB": "At 'Bossware and Employment Tech Database' (T1, eight cards: B1–B8; B3, B5 and B8 not found, B4 and B6 refused by bot check, B7 fetched with its title only; 231 words) the composition gives the database by its operator's page and places another study beside it. Composed from its cards: the definition at the page's grain (B1 F1, 'more than 550 labor-focused technology products', the operator named attributively, CAP-1-13), with the page's 'manage employees and collect their data' (F13) coarsened to 'monitor, track, and manage workers'; the term at the New York Times snippet's grain (B5 F40), its 'surveil, and track' folded into 'supervise' and 'physical locations' added, under an unresolved marker; four kinds of feature at the grain of B1's table rows (keystrokes, mouse activity, screenshots, webcams, GPS and facial recognition occur in its rows; 'active window focus' in no field source); thirteen products, every one a row of B1's table (CAP-1-01, confirmed against the saved table). Substituted reading: the groups. T's three headings are not the table's categories: Amazon's Project Ultraviolet (Covid-19 testing), Mentor App and Fulfilment Center WiFi Tracking, and 'Amazon.com - Netradyne Vehicle Surveillance', are Workplace Safety rows, and Alice Housekeeping a Workplace Performance/Productivity Monitoring row (B1 table; F15 the report's four areas); T gathers them as 'Industry-Specific & Logistics Tracking' and gives Netradyne apart from the Amazon tools whose row it is. The markers show a second join: the heading 'The Coworker Worktech Database tracks a wide range of platforms' carries card 1's token, and its first group, 'ActivTrak, Hubstaff, Time Doctor, Desklog, and Controlio', carries card 2's as well; Hubstaff, Time Doctor and Desklog are in B1's table and in card 2's sample of nine (F48), so another study's sample is folded into the database's examples at the grain of product names. 'Productivity Scoring' and 'Hiring & AI Analytics' carry card 3's token, a video post read by its title only. Limit dropped, and force raised by tense: 'catalogs' and 'tracks' (CAP-1-04) give in the present an inventory the page dates 17 November 2021 (F3) and the report dates November 2020 to May 2021 (F4); two of the products T names are Discontinued in the table, Amazon's warehouse WiFi tracking (F19) and HireVue's AI facial recognition (F18), which T gives as current examples. Limit dropped: 'not exhaustive', the omissions and the product level (F31, F32; CAP-1-05), and the reliance on public documents and stated uses (F33, F34). Assigned to another (at the grain of institutions): the privacy paragraph is card 2's study (F46, F51–F53; CAP-1-06), credited to 'institutions like Vanderbilt Law School', the card's host; the study's authors are at four institutions (F49) and its subject is nine monitoring platforms of which only some are the database's rows (F48). Substituted reading: 'deep data profiles (including personal emails, device data, and location records)' where the study reports identifying data (first name, last name, an email address, company), online activity and location features (F51–F53). Available, not composed: the date and research period (F3–F5); the report, its author and its name for the marketplace, Little Tech (F7–F11, a link on card 1's page); the purpose and the investors (F12, F14; CAP-1-11); the worker-rights criteria (F21, F22) and the 35% privacy finding (F23; CAP-1-05); the report's findings (F25–F30); the stories invited (F36, F37); the operator's self-description (F38); the four areas and the report's 40% and 38% (F15, F16); from card 2, its authors, method, date and recommendations (F47, F49, F50, F54, F55); from card 3's title, the 70% (F42). Composed without attribution: no person is named (CAP-1-13), at the coarse grain of a database description (recorded, not a breach). Content replaced by use: the closer (T1-12).", "T_vs_LB_reading": "v0.9 §0.5: the first diff is ontological in a narrow, exact way. T and the field agree on the entity (Coworker's inventory of workplace technology products); T composes the inventory as a live catalogue of the class it names, its examples read off the table without the table's date, status or categories, and sets beside it, under the database's own heading, another study's sample and findings. What the database is for, assessing each product against worker-rights criteria and reporting the harm, and what it says it is not, are left on the card's page.", "LB_vs_LBA": "Admission adds, in one claim space with the field's: the census's answer to its organizing question, who supplies the labor, who directs it and who receives its gains, read from the table's own fields (LV-30, LV-05–LV-08), beside the report's statement that costs are shifted onto workers (F26), the census's basis for its gains field; its intersections, AI governing labor first (LV-02, LV-31); the unit and the kinds of evidence (LV-03, LV-04); the census's tally of the saved table and its unchecked items, among them the report's 40% and 38% not reproduced by the table (LV-13, LV-28, LV-29), held against F16 under P_coh; what this evidence can and cannot settle (LV-15, LV-16); the lifecycle and the negative tags (LV-21–LV-26); the archive's reading of where the database meets Labor Vector's instruments, the layer of who directs labor, with no measurement for DSL or task-origin (LV-17, LV-18); the class reading of #747, in which hiring and screening technology, AI interview platforms such as HireVue among it, produce calibration intelligence from candidates' uncompensated labor, with #747's own limits (O747-01–O747-07); and the Capture Registry's account of the composition at the name (CAP-1-01–CAP-1-13). Not surfaced: every archive source; no card cites the census record (CAP-1-10).", "alignment": { "T1_cards_claims": [ "F1", "F3", "F6", "F7", "F8", "F12", "F13", "F14", "F17", "F18", "F19", "F20", "F21", "F22", "F36", "F38", "F40", "F41", "F42", "F43", "F44", "F45", "F46", "F47", "F48", "F49", "F50", "F51", "F52", "F53", "F54", "F55" ], "T1_composed": [ "F1", "F13", "F40", "F17", "F18", "F46", "F51", "F52", "F53", "F48" ], "T1_composed_note": "F1 at its grain ('more than 550 labor-focused technology products'); F13 coarsened ('manage employees' as 'monitor, track, and manage workers'); F40 at the snippet's grain, 'surveil, and track' folded into 'supervise' and 'physical locations' added; F17/F18 as 'HireVue (voice and interview analysis)', the status Discontinued not composed; F46, F51–F53 at a coarse grain ('deep data profiles … and share them'); F48 in part (Hubstaff, Time Doctor, Desklog, which are also rows of B1's table, under card 2's marker in T1-8). The thirteen products T1-8–T1-10 name are rows of B1's table (CAP-1-01, verified against the saved table): ledgered at F17–F19 for the two whose status bears on the delta", "T1_outside_cards": [ "T1-3 'active window focus' (no field source; the table's rows carry keystrokes, mouse activity, screenshots and webcams)", "T1-9 'Industry-Specific & Logistics Tracking' (not a category of the table or the report; the Amazon tools and Netradyne are 'Workplace Safety' rows, Alice Housekeeping a 'Workplace Performance/Productivity Monitoring' row)", "T1-11 'personal emails' (B2 reports an email address among identifying data, F51)", "T1-12 'state disclosure laws' (no field source)" ], "rule": "T against L_F(B): the field claims of the cards T surfaced (B1–B8), aligned to T's claims by quote and grain; the own page (B9) and Wikipedia (B10) are in L_F(B) but were not surfaced by T. A field claim counts as composed when T states it at its source's grain or coarser" } }, "kernel": [ { "K": "K1", "claim": "`LV-01`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "what it is: Coworker.org's database of more than 550 labor-focused technology products", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F1)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K2", "claim": "`LV-12`", "source": "Labor Vector census record, 2026-10-29", "M_src": "documented", "sense": "what it is: Coworker.org's database of more than 550 labor-focused technology products", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F1; the 635 rows are the census's count)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K3", "claim": "`LV-11`", "source": "Labor Vector census record, 2026-10-29", "M_src": "documented", "sense": "publication and the research period", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F4, F5)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K4", "claim": "`LV-02`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "the census's question: who supplies the labor, who directs it, who gains", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K5", "claim": "`LV-31`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "the census's question: who supplies the labor, who directs it, who gains", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K6", "claim": "`LV-30`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "the census's question: who supplies the labor, who directs it, who gains", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K7", "claim": "`LV-06`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "the census's question: who supplies the labor, who directs it, who gains", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K8", "claim": "`LV-05`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "the census's question: who supplies the labor, who directs it, who gains", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F35, F13)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K9", "claim": "`LV-07`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "the census's question: who supplies the labor, who directs it, who gains", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K10", "claim": "`LV-08`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "the census's question: who supplies the labor, who directs it, who gains", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F26)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K11", "claim": "`LV-04`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "the assessment of each product's data practices against worker-rights criteria", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F21, F22)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K12", "claim": "`LV-03`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "the census's question: who supplies the labor, who directs it, who gains", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K13", "claim": "`LV-13`", "source": "Labor Vector census record, 2026-10-29", "M_src": "documented", "sense": "the table: categories, products and their status", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "rival claim (F16: 40% and 38%)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K14", "claim": "`LV-28`", "source": "Labor Vector census record, 2026-10-29", "M_src": "self-description", "sense": "the table: categories, products and their status", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "rival claim (F16)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K15", "claim": "`LV-29`", "source": "Labor Vector census record, 2026-10-29", "M_src": "self-description", "sense": "the table: categories, products and their status", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K16", "claim": "`LV-19`", "source": "Labor Vector census record, 2026-10-29", "M_src": "documented", "sense": "the table: categories, products and their status", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F20)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K17", "claim": "`LV-20`", "source": "Labor Vector census record, 2026-10-29", "M_src": "documented", "sense": "the accompanying report and its name for the marketplace, Little Tech", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F10)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K18", "claim": "`O747-01`", "source": "#747", "M_src": "definition", "sense": "the archive's category on the class: hiring and screening as production", "qualifiers carried": "O747-06, O747-07", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K19", "claim": "`O747-03`", "source": "#747", "M_src": "interpretation", "sense": "the archive's category on the class: hiring and screening as production", "qualifiers carried": "O747-06, O747-07", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F17, F18: the table's HireVue row)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K20", "claim": "`O747-02`", "source": "#747", "M_src": "definition", "sense": "the archive's category on the class: hiring and screening as production", "qualifiers carried": "O747-06, O747-07", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K21", "claim": "`O747-04`", "source": "#747", "M_src": "interpretation", "sense": "the archive's category on the class: hiring and screening as production", "qualifiers carried": "O747-06, O747-07", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K22", "claim": "`O747-05`", "source": "#747", "M_src": "interpretation", "sense": "the archive's category on the class: hiring and screening as production", "qualifiers carried": "O747-06, O747-07", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K23", "claim": "`O747-06`", "source": "#747", "M_src": "fact", "sense": "the archive's category on the class: hiring and screening as production", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K24", "claim": "`O747-07`", "source": "#747", "M_src": "fact", "sense": "the archive's category on the class: hiring and screening as production", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K25", "claim": "`LV-09`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "stated limits: not exhaustive, product level, public documents", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F33)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K26", "claim": "`LV-10`", "source": "Labor Vector census record, 2026-10-29", "M_src": "documented", "sense": "stated limits: not exhaustive, product level, public documents", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F31)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K27", "claim": "`LV-14`", "source": "Labor Vector census record, 2026-10-29", "M_src": "self-description", "sense": "stated limits: not exhaustive, product level, public documents", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F31)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K28", "claim": "`LV-24`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "stated limits: not exhaustive, product level, public documents", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F31)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K29", "claim": "`LV-26`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "stated limits: not exhaustive, product level, public documents", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F32)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K30", "claim": "`LV-21`", "source": "Labor Vector census record, 2026-10-29", "M_src": "documented", "sense": "publication and the research period", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F3, F4)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K31", "claim": "`LV-22`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "what it is not", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F34)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K32", "claim": "`LV-25`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "what it is not", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F3)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K33", "claim": "`LV-15`", "source": "Labor Vector census record, 2026-10-29", "M_src": "interpretation", "sense": "what this evidence can and cannot settle", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K34", "claim": "`LV-16`", "source": "Labor Vector census record, 2026-10-29", "M_src": "interpretation", "sense": "what this evidence can and cannot settle", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F34)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K35", "claim": "`LV-23`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "workers' stories and what they would supply", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "qualified claim (F36)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K36", "claim": "`LV-17`", "source": "Labor Vector census record, 2026-10-29", "M_src": "interpretation", "sense": "where it meets Labor Vector's instruments", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K37", "claim": "`LV-18`", "source": "Labor Vector census record, 2026-10-29", "M_src": "interpretation", "sense": "where it meets Labor Vector's instruments", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing distinction (the field has no claim on the point)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K38", "claim": "`LV-27`", "source": "Labor Vector census record, 2026-10-29", "M_src": "stipulation", "sense": "neighbour: the UC Berkeley Labor Center's list", "qualifiers carried": "LV-28, LV-29", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "none (one lineage with F39)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3); and a later read of the entity's pages by the Labor Vector census" }, { "K": "K39", "claim": "`CAP-1-09`", "source": "Capture Registry, 2026-10-29", "M_src": "interpretation", "sense": "the composition at the name: what it held", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K40", "claim": "`CAP-1-01`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the composition at the name: what it held", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K41", "claim": "`CAP-1-02`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the composition at the name: what it held", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K42", "claim": "`CAP-1-13`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the composition at the name: what it held", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K43", "claim": "`CAP-1-12`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the composition at the name: what it held", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K44", "claim": "`CAP-1-03`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the composition at the name: a 2021 inventory given as current", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K45", "claim": "`CAP-1-04`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the composition at the name: a 2021 inventory given as current", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K46", "claim": "`CAP-1-07`", "source": "Capture Registry, 2026-10-29", "M_src": "interpretation", "sense": "the composition at the name: a 2021 inventory given as current", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K47", "claim": "`CAP-1-08`", "source": "Capture Registry, 2026-10-29", "M_src": "interpretation", "sense": "the composition at the name: a 2021 inventory given as current", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K48", "claim": "`CAP-1-05`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the composition at the name: the database's limits unsaid", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K49", "claim": "`CAP-1-11`", "source": "Capture Registry, 2026-10-29", "M_src": "interpretation", "sense": "the composition at the name: the database's limits unsaid", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K50", "claim": "`CAP-1-06`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "the composition at the name: another study's finding beside the database", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" }, { "K": "K51", "claim": "`CAP-1-10`", "source": "Capture Registry, 2026-10-29", "M_src": "documented", "sense": "reception: the record and the cards", "qualifiers carried": "—", "f (source's own falsifiers)": "— (none stated; watch: a later composition at the address that states or drops the claim, attributed or not, uptake §8.3)", "contrast": "missing finding (an observation of the composition at the entity's address)", "resolver": "a later capture at 'Bossware and Employment Tech Database' (ADDR-bc5215fba8fa) on Google AI Overview, seated in the Capture Registry (§8.3)" } ], "kernel_T": [ { "claim": "F3", "note": "the page's date, 17 November 2021, absent; the database given in the present tense" }, { "claim": "F4", "note": "the research period, November 2020 to May 2021, absent" }, { "claim": "F18", "note": "HireVue's AI facial recognition row is Discontinued; T gives HireVue as a current example" }, { "claim": "F19", "note": "Amazon's warehouse WiFi tracking row is Discontinued; T gives it as a current example" }, { "claim": "F31", "note": "not exhaustive; non-U.S. and emerging products omitted (limit dropped)" }, { "claim": "F32", "note": "the product level and the omitted gig platforms (limit dropped)" }, { "claim": "F21", "note": "the worker-rights criteria each row is assessed against, absent" }, { "claim": "F23", "note": "the 35% privacy finding, absent" }, { "claim": "F9", "note": "the report and its name for the marketplace, Little Tech, absent" }, { "claim": "F25", "note": "the report's first finding, absent; the harm carried only through another study" }, { "claim": "F12", "note": "the investors the database lists beside the products, absent" }, { "claim": "F49", "note": "the other study's four institutions; T credits 'institutions like Vanderbilt Law School'" } ], "ledger": { "archive": "datasets/negative-of-the-negative/v2/ledgers/coworker-bossware-database/ledger-archive.json", "field": "datasets/negative-of-the-negative/v2/ledgers/coworker-bossware-database/field.json", "selection": "datasets/negative-of-the-negative/v2/traversal/coworker-bossware-database/", "config": "datasets/negative-of-the-negative/v2/panel/configs/coworker-bossware-database.json", "intake": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/", "audit": null }, "ontology": { "composition": "equal", "composition_note": "equal-terms case (v0.9 §0.9, §4.1): one claim space; the field's and the archive's claims ordered together by the entity's dependency and by genealogy within each sense; nothing translated; F16 against LV-13/LV-28 held under P_coh; #747's class reading held beside the table's hiring rows", "case": { "value": "equal", "statement": "The archive reads the field's entity as the entity. The Labor Vector census record describes the database from its operator's own pages, each field with its evidence and basis ('operator', or 'observed' for the table's counts), and answers for it the census's question of who supplies the labor, who directs it and who receives its gains, reading the answer from the table's own fields; its lv_intersection is the archive's reading, kept apart from the resource's terms, and places the database at the layer of who directs labor while finding no measurement in it for DSL or task-origin. The capture record checks the composition against the census and its saved sources (CAP-1-01–CAP-1-02). No deposit names the database. One deposit bears on a class the field sources for it, hiring and screening technology (the database's category Labor Market Optimization, its HireVue row; the report's taxonomy), and adds a sense on the field's own object: screening as production, in which candidates' uncompensated labor becomes the operator's calibration intelligence and AI interview platforms such as HireVue capture candidates' data as institutional capital (#747), a structural reading that 'reads what that apparatus measured' and alleges no illegality. No defining paper or record contests the field's ontology of the database or supplies one the field lacks: ρ = extends, the equal-terms case (§0.9, §1.2a). The archive's instruments of labor direction (#771, #1392) are defined on synthetic labor and bear here only through the census's reading.", "loci": [ { "dep": "LV", "locus": "census.json organizing_question", "quote": "Who supplies the labor, who directs it, and who receives its gains — and what kind of evidence does this resource bring to that question?" }, { "dep": "LV", "locus": "census.json schema_note", "quote": "lv_intersection (where it meets DSL, task-origin and user labor drag: the archive's reading, kept apart from the resource's own terms)" }, { "dep": "LV", "locus": "census.json rows[slug == 'coworker-bossware-database'].lv_intersection", "quote": "The database inventories the products through which employers direct work and collect workers' data, product by product; it meets the directionality stack at the layer of who directs labor." }, { "dep": 747, "locus": "§I s1–3", "quote": "This paper is a structural reading. It does not duplicate the empirical apparatus of ERS-001 v0.6; it reads what that apparatus measured." }, { "dep": 747, "locus": "§VIII, list item 'AI interview platforms'", "quote": "- **AI interview platforms.** Firms like HireVue, Karat, and emerging AI-mediated interview operators. These collect video, audio, response timing, and behavioral data from candidates at scale. The captured data is institutional capital. The candidates' labor is supplied free." }, { "dep": 771, "locus": "Abstract s2", "quote": "Both are silent on a third dimension: the *direction* in which a synthetic system's labor flows relative to the task its user commissioned." }, { "dep": "capture", "locus": "bossware-and-employment-tech-database-aio-20261029, analysis s1", "quote": "A 2021 inventory is composed as a live catalogue, with a later third-party study placed beside it." } ] }, "E_F": { "type": "C (public entity: a database of workplace technology products and the report that accompanies it)", "definition": "Coworker.org's Bossware and Employment Tech database (home.coworker.org/worktech/), dated 17 November 2021: more than 550 labor-focused technology products, catalogued as products and not companies, researched November 2020 to May 2021 (31% emerging in 2020 to 2021), that touch the labor process from hiring to productivity monitoring and use AI, location tracking and biometrics to manage employees and collect their data, often without their knowledge; each row assessed against worker-rights criteria (informed consent, workers' access to and correction of their data, grievance, forced use, discrimination, freedom of association), only 35% sharing any privacy information; sorted into four areas; accompanied by the report Little Tech Is Coming for Workers (Wilneida Negrón, PhD; © 2021 Coworker.org, CC BY-NC-ND 4.0), which names the marketplace Little Tech and finds the products eroding labor standards and worker power and shifting costs onto workers; not exhaustive, built at the product level with the gig platforms omitted, resting on public documents; beside it in the field, the term bossware as press and video give it, and a 2026 study of nine monitoring platforms that shared workers' data", "claims": [ "F1", "F3", "F4", "F5", "F2", "F12", "F13", "F21", "F22", "F23", "F15", "F7", "F8", "F10", "F9", "F25", "F26", "F31", "F32", "F33", "F40", "F46" ] }, "E_A": { "definition": "the same database, in the Labor Vector census record and the archive's deposits: a database whose unit is a labor-focused technology product and whose evidence is a product inventory and a rating against standards, read under AI governing labor, gains and losses, and worker power, and answering the census's question from its own fields: the labor supplied by the workers each product targets, directed by the employers who buy and deploy the products through their vendors, its gains to the vendors and investors each row names; historical, not exhaustive, not a measure of deployment, not worker testimony; able to settle which products existed in 2020 to 2021 and what their documents say, and not how they are used or with what effect; meeting the directionality stack at the layer of who directs labor, with no measurement for DSL or task-origin (census record); its hiring products members of a class the archive reads as production, screening turning candidates' uncompensated labor into the operator's calibration intelligence, AI interview platforms such as HireVue capturing candidates' data as institutional capital (#747); and, at its name, a 2021 inventory composed as a live catalogue with another study beside it (Capture Registry)", "claims": [ "LV-01", "LV-04", "LV-03", "LV-02", "LV-30", "LV-06", "LV-07", "LV-08", "LV-21", "LV-24", "LV-22", "LV-23", "LV-15", "LV-16", "LV-17", "LV-18", "O747-01", "O747-02", "O747-03", "CAP-1-07" ], "defining_papers": [ 747 ], "defining_records": [ "Labor Vector census record (census.json rows[slug == 'coworker-bossware-database'], organizing_question, intersections, schema_note; rendered aggregators/coworker-bossware-database/index.html; editor Lee Sharks, compiled 2026-10-29, schema 1.0)", "Capture Registry bossware-and-employment-tech-database-aio-20261029 (OBS-ac3acd79e5f3)" ] }, "rho": { "value": "extends", "status": "read from the Labor Vector census record, the capture record and the deposit that bears on the class (§1.2a); no deposit names the database; #747 states itself a structural reading of what an apparatus measured, alleging no illegality", "statement": "the archive reads E_F as the entity and adds senses and limits on the field's own object: the census's answer, from the table's own fields, to who supplies, directs and gains (LV-30, LV-05–LV-08); its intersections, unit and kinds of evidence (LV-02–LV-04, LV-31); its tally and unchecked items, the report's percentages held against the table (LV-13, LV-28, LV-29); what the evidence can and cannot settle (LV-15, LV-16); the negative tags (LV-21–LV-26); the meeting with Labor Vector's instruments at the layer of who directs labor (LV-17, LV-18); hiring technology read as production (O747-01–O747-07); the composition's account at the name (CAP-1-01–CAP-1-13)", "claims": [ "LV-30", "LV-06", "LV-07", "LV-08", "LV-02", "LV-03", "LV-04", "LV-13", "LV-28", "LV-15", "LV-16", "LV-22", "LV-23", "LV-25", "LV-17", "LV-18", "O747-01", "O747-02", "O747-03", "O747-06", "CAP-1-04", "CAP-1-07" ], "guard": "ρ = extends claims an addition and no more (§1.2a): the archive does not say Coworker's records are wrong, and #747's categories are applied by the archive to the class (hiring and screening technology), HireVue named in both, not to the database, which #747 does not name, and with #747's own limits (no individual design, no illegality, no culpable party). Where an archive record stands against a field claim (LV-13 and LV-28, the table's 176 and 242 of 635, against F16, the report's 40% and 38%), both are composed under P_coh within the one ontology, each with its source. The census's reading of direction (LV-17, LV-18) is the archive's and is composed as such, beside the resource's own terms.", "considered": [ { "value": "constructs", "reason": "no defining paper or record reads the database as made by its reception; the census and the capture take the operator's pages as the entity's own account" }, { "value": "revises", "reason": "the database is not the archive's own entity; the archive has no earlier statement of it" }, { "value": "witness case", "reason": "the field holds the ontology (a database of products assessed against worker-rights criteria); the archive supplies no ontology the field lacks for it" } ] }, "translation": [ { "lineage": "what it is: Coworker.org's database of more than 550 labor-focused technology products", "field_claims": [ "F1", "F2" ], "received": "F1 (B1, header, ¶1 s3): \"Coworker.org’s Bossware and Employment Tech database compiles more than 550 labor-focused technology products that are changing our relationship to work.\"; F2 (B9, Introduction, left column ¶3): \"Our research has identified more than 550 … products, which we’ve assembled into a … searchable database and dubbed Little Tech;\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-01, LV-12", "archive_claims": [ "LV-01", "LV-12" ] }, { "lineage": "publication and the research period", "field_claims": [ "F3", "F4", "F5" ], "received": "F3 (B1, header, dateline): \"NOVEMBER 17, 2021 | COWORKER.ORG\"; F4 (B9, The Scope of the Study, left column ¶1 s1): \"Our research, which ran from November 2020 … until May 2021, catalogued more than 550 … products (not the companies that created … them) that are currently interfacing with low-\"; F5 (B9, The Scope of the Study, right column ¶2): \"Thirty-one percent of the products listed … emerged between 2020 and 2021; the rest … were developed between 2018 and 2020.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-11, LV-21", "archive_claims": [ "LV-11", "LV-21" ] }, { "lineage": "scope: the whole labor process, products and investors; AI, location tracking and biometrics", "field_claims": [ "F6", "F12", "F13", "F14" ], "received": "F6 (B1, header, ¶1 s1–2): \"Could your boss be an app? Since 2018 we’ve seen a rise in the use of tech to manage the world’s labor force.\"; F12 (B1, header, ¶4 s1): \"In the database you’ll find companies — and their products and investors — that touch every part of the labor process, from hiring to productivity monitoring and more.\"; F13 (B1, header, ¶4 s2): \"Organized by category, type, and date founded, the database covers products that use technology like AI, location tracking, and biometrics to manage employees and collect their data — often without their knowledge.\"; F14 (B1, header, ¶5): \"Use the table and the filters below to learn more about the companies behind this emerging trend:\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-02, LV-31, LV-17", "archive_claims": [ "LV-02", "LV-31", "LV-17" ] }, { "lineage": "the accompanying report and its name for the marketplace, Little Tech", "field_claims": [ "F7", "F8", "F9", "F10", "F11" ], "received": "F7 (B1, header, ¶2): \"Little Tech Is Coming for Workers , an accompanying report, seeks to address the proliferation of these technologies and analyzes the ways they’re harming workers, labor standards, and the economy.\"; F8 (B1, the report's download block): \"Little Tech is Coming for Workers A Framework for Reclaiming and Building Worker Power By Wilneida Negrón, PhD\"; F9 (B9, Executive Summary, left column ¶3 and right column ¶1): \"Coworker’s analysis of more than 550 tech … products, companies, and investors reveals an … ecosystem of tech products, companies, and … investors we dub “Little Tech”; the unregulat- … ed marketplace of tech products that are col- … lecting and aggregating data about workers at … almost every step of the labor process\"; F10 (B9, p. 3, colophon): \"Little Tech Is Coming for Workers: A Framework for Reclaiming and Building Worker Power, © 2021 by Coworker.org, is licensed under Attribution NonCommercial-NoDerivatives 4.0 International.\"; F11 (B9, p. 3, Acknowledgements ¶2): \"An extra special shoutout to Ayden Federline for meticulously and graciously researching and creating the database of employment tech products.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-20", "archive_claims": [ "LV-20" ] }, { "lineage": "the table: categories, products and their status", "field_claims": [ "F15", "F16", "F17", "F18", "F19", "F20" ], "received": "F15 (B9, The Scope of the Study, p. 24, the four areas): \"1. Workplace performance, productivity monitoring 2. Workplace safety 3. Workplace benefits, health, and well-being 4. Labor, job market, and workplace optimization\"; F16 (B9, The Scope of the Study, p. 26, left column ¶1): \"Based on this taxonomy, we found that most … products are either trying to promote work- … place safety (40%) or optimize the functioning … of the labor markets (38%).\"; F17 (B1, table, row 'HireVue AI Facial Recognition' (Product Name through Type)): \"HireVue AI Facial Recognition HireVue, Inc https://www.hirevue.com/ HireVue's Hiring Intelligence Platform claims to deliver the best talent, faster, with video interviews and AI-driven pre-hire assessments No Labor Market Optimization App or Software\"; F18 (B1, table, row 'HireVue AI Facial Recognition' (Current Business Goals, end, and Status)): \"Their behavior, intonation, and speech is fed to an algorithm that assigns certain traits and qualities Discontinued\"; F19 (B1, table, row 'Amazon.com - Fulfilment Center WiFi Tracking' (Product Name through Status)): \"Amazon.com - Fulfilment Center WiFi Tracking Amazon.com Inc https://www.amazon.com/ Amazon is an international e-commerce website for consumers, sellers, and content creators Yes Workplace Safety Hardware Hourly, non-management * Gives Amazon a way to track workers’ locations inside warehouses so they can develop better social distancing and cleanliness plans Discontinued\"; F20 (B1, table header and instruction): \"Click the \"+\" next to the product name to expand the table.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-13, LV-19, LV-28, LV-29, O747-03, CAP-1-01", "archive_claims": [ "LV-13", "LV-19", "LV-28", "LV-29", "O747-03", "CAP-1-01" ] }, { "lineage": "the assessment of each product's data practices against worker-rights criteria", "field_claims": [ "F21", "F22", "F23", "F24" ], "received": "F21 (B1, table header, columns 30–32): \"Informed consent obtained Can the worker access and interpret their own data? Can the worker correct incorrect data?\"; F22 (B1, table header, columns 37–40): \"Grievance mechanism Forced use of tool Discrimination potential Right to freedom of association\"; F23 (B9, Economic Drivers and Political Context, p. 33, left column): \"Only 35% of the products share any information on privacy policy and data sharing arrangements.\"; F24 (B9, The Scope of the Study, p. 26, left column ¶3): \"Central to our analysis was needing to move … beyond a privacy-only framework and begin\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-04", "archive_claims": [ "LV-04" ] }, { "lineage": "findings: labor standards, worker voice and power, costs shifted onto workers", "field_claims": [ "F25", "F26", "F27", "F28", "F29", "F30" ], "received": "F25 (B9, Executive Summary, finding 1 (heading)): \"1. The current proliferation of tech products has the potential to continue eroding labor standards and weaken worker voice and worker power, while also increasing the potential for discrimination and other harms.\"; F26 (B9, Executive Summary, finding 1, left column bullet 1): \"they are contributing to the ongoing … reduction of labor standards,5 continu- … ing to shift the costs of production onto … workers6, and fissuring labor markets.7\"; F27 (B9, Executive Summary, finding 1, right column bullet 3): \"Accelerating the commodification of … low-wage workers’ data, particularly\"; F28 (B9, Executive Summary, finding 2 (heading)): \"2. A historic amount of private capital is contributing to the proliferation of tech products to be used in the workplace and in the labor markets.\"; F29 (B9, Table of Contents, p. 67 entry): \"Low-wage workers must navigate scientifically questionable hiring … and background check technologies.\"; F30 (B9, Conclusion, left column ¶1 s1–2): \"This report explores the implications of more … than 550 technology products that have … appeared in the workplace and job markets … during the pandemic.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-08", "archive_claims": [ "LV-08" ] }, { "lineage": "stated limits: not exhaustive, product level, public documents", "field_claims": [ "F31", "F32", "F33", "F34", "F35" ], "received": "F31 (B9, The Scope of the Study, left column ¶2): \"note that the database is not exhaustive, … and we omitted or overlooked hundreds … more products that were still emerging or in … development as well as non-U.S. products. … We stopped collecting information once … we felt we had sufficient evidence of the … pervasiveness of Little Tech as well as a\"; F32 (B9, Executive Summary, footnote 2): \"Please note that we do omit from this analysis smaller Big Tech companies, such as Twitter, Airbnb, Uber, Lyft, DoorDash, InstaCart, GrubHub, Care.com, and Handy, as we developed the database at the product and not company level, and we were looking at products that had emerged in the workplace in the past one to two years.\"; F33 (B9, footnote 66): \"Investor information was obtained from Crunchbase. For app permissions and hardware usage data, we have relied on the data available in the Google Play store for Android devices. In assessing the privacy implications of a product, we have relied on publicly accessible privacy statements, terms of service documents, and public impact assessments.\"; F34 (B9, Executive Summary, finding 5, right column ¶1): \"context for how these technologies are actu- … ally implemented in the workplace (rather than … relying on the products’ stated use/purposes … and business goals).\"; F35 (B9, The Scope of the Study, left column ¶1 s2): \"report primarily discusses the experience of … low-wage and hourly workers, because these\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-09, LV-10, LV-14, LV-24, LV-26", "archive_claims": [ "LV-09", "LV-10", "LV-14", "LV-24", "LV-26" ] }, { "lineage": "workers' stories and what they would supply", "field_claims": [ "F36", "F37" ], "received": "F36 (B1, header, worker invitation): \"are you a worker who interacts with any of the tech in our database? … Click here to share your story with our team .\"; F37 (B9, Executive Summary, finding 5 (heading)): \"5. Listing, classifying, and analyzing Little Tech’s direct harms can build worker voice and power and strengthen regulatory efforts.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-23", "archive_claims": [ "LV-23" ] }, { "lineage": "the operator: Coworker.org", "field_claims": [ "F38" ], "received": "F38 (B1, footer, the operator's statement): \"Coworker.org is a global platform to advance change in the workplace.\"", "receiving_text": "—", "translation": "untranslated: composed as received (no archive claim on the lineage)", "archive_claims": [] }, { "lineage": "neighbour: the UC Berkeley Labor Center's list", "field_claims": [ "F39" ], "received": "F39 (B9, The Scope of the Study, p. 26, left column ¶2): \"UC Berkeley Labor Center’s list in their report\"", "receiving_text": "—", "translation": "untranslated: composed as received beside LV-27", "archive_claims": [ "LV-27" ] }, { "lineage": "the term bossware, in press and video", "field_claims": [ "F40", "F41", "F42", "F43", "F44", "F45" ], "received": "F40 (B5, card title and snippet): \"Definition: \"Bossware\" refers to technology and AI tools used by managers to supervise, surveil, and track employee habits, output, and biometrics across indust...\"; F41 (B6, card title): \"How Bossware is Watching While You Work\"; F42 (B3, card title): \"Bossware Workplace Surveillance: 70% of U.S. Employers Track Workers\"; F43 (B4, card title): \"Pwning Bossware for Fun and Ethics\"; F44 (B7, card title (and the page's script data)): \"What’s the Deal with Bossware?\"; F45 (B8, card title): \"Is your boss watching you right now? 👁️ #bossware #privacy #worklife\"", "receiving_text": "—", "translation": "untranslated: composed as received (no archive claim on the lineage)", "archive_claims": [] }, { "lineage": "another study: workplace monitoring platforms share workers' data (Northeastern, Vanderbilt, Berkeley, Columbia, 2026)", "field_claims": [ "F46", "F47", "F48", "F49", "F50", "F51", "F52", "F53", "F54", "F55" ], "received": "F46 (B2, ¶1 s1): \"A new investigation finds that workplace monitoring platforms are systematically sharing personal data about workers and online activity with hundreds of outside data brokers and big tech companies in ways that are not clearly disclosed and that, in some cases, may contradict the platforms’ own privacy policies.\"; F47 (B2, dateline): \"May 27, 2026, 12:47 PM\"; F48 (B2, ¶1 s2): \"The researchers examined nine widely used workplace monitoring platforms — Apploye, Deputy, Desklog, Hubstaff, Monitask, Buddy Punch, Time Doctor 2, Vericlock, and When I Work, tracking how each app collects and shares worker data in practice.\"; F49 (B2, ¶2 s1): \"The report was authored by researchers at the Khoury College of Computer and Information Sciences at Northeastern University; the Vanderbilt Policy Accelerator at Vanderbilt University; the Center for Consumer Law and Economic Justice at UC Berkeley Law School; and the Center for Law and the Economy at Columbia Law School.\"; F50 (B2, What Researchers Found, ¶1): \"by signing up as an employer, setting up bossware services for workers, then logging in as an employee.\"; F51 (B2, What Researchers Found, 'Worker data shared'): \"All (9 of 9) workplace monitoring platforms directly shared identifying worker data including first name, last name, email, and company to third parties. … The researchers recorded 121 unique instances of worker data being shared with companies including Facebook, Google, Microsoft, and AppLovin (a mobile advertising platform).\"; F52 (B2, What Researchers Found, 'Online activity shared'): \"The 9 workplace monitoring platforms in the sample shared information about workers’ online activities (such as IP address, device information, web pages visited, unique identifiers, etc.) to a total of 145 unique third-party domains\"; F53 (B2, What Researchers Found, 'Location tracking'): \"One third of the workplace monitoring platforms in the sample have features that track workers’ precise location at any time – even when the app is in the background or potentially when the worker is clocked out.\"; F54 (B2, ¶ quotation, Sitaraman): \"“‘Bossware’ is increasingly common in jobs of all kinds, and workers likely have no idea that their data is being systemically collected and distributed to unknown data brokers and tech companies,” said Ganesh Sitaraman, Director at Vanderbilt Policy Accelerator.\"; F55 (B2, A Call for Urgent Policy Action, ¶1): \"The report argues that protections currently in place to protect workers from employee surveillance, including sharing of their workplace data, are insufficient. … Key recommendations include banning the sale or sharing of worker data, prohibiting unlimited data retention, and barring collection of sensitive employee information.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside CAP-1-06", "archive_claims": [ "CAP-1-06" ] }, { "lineage": "reception: the encyclopedia", "field_claims": [ "F56" ], "received": "F56 (B10, Wikipedia: title Bossware_and_Employment_Tech_Database; title Coworker.org; article-space searches): \"raw wikitext, title Bossware_and_Employment_Tech_Database (action=raw, redirect=no), 2026-10-29T22:38:52Z: HTTP 404 … Wikipedia does not have an article with this exact name. … raw wikitext, title Coworker.org (the operator; action=raw, redirect=no), 2026-10-29T22:39:03Z: HTTP 404 … There were no results matching the query.\"", "receiving_text": "—", "translation": "untranslated: composed as received beside CAP-1-10", "archive_claims": [ "CAP-1-10" ] } ], "receiving_texts": "equal-terms case: every field claim composed as received, beside the archive claims it stands with" }, "measure": { "rule": "v0.9 §4.10: KO_B sentences surviving in the KO at similarity ≥ 0.95, with positions (computed as apply_v09.py does: difflib.SequenceMatcher ratio, the best KO sentence for each KO_B sentence)", "v0.9": { "surviving": 0, "of": 12, "positions": [ null, null, null, null, null, null, null, null, null, null, null, null ] }, "opening_run": { "rule": "v0.9 §5.10 (equal-terms case): the field-only KO's sentences as the KO's opening run in their own order", "breach": false }, "blocks": { "rule": "v0.9 §4.1 (equal-terms and mixed cases): the KO does not open with the field as a block or close with the archive as one; sentences typed by the ledgers of the claims they cite (F field-only, A archive-only, M both)", "sequence": "MMFAMAFMFMFFFFAAAFMAAMAMFFFAMM", "field_only_head": 0, "archive_only_tail": 0, "breach": false }, "max_similarity": [ 0.29, 0.072, 0.31, 0.13, 0.359, 0.262, 0.089, 0.141, 0.227, 0.464, 0.227, 0.264 ], "ko_sentence_1_max_similarity_to_KO_B": 0.29 }, "homonyms": { "names": [], "basis": "The census row carries no disambiguation field, and the Labor addendum names no homonym in this row's T. No card is a homonym: all eight cards concern bossware. Card 1 is the entity; card 2 is another study of the class (a distinct entity, below); cards 3–8 concern the term. 'Bossware' is the class the database's name carries, not a sense of the name; 'Coworker Worktech Database' (T1-7) is a variant the composition took from the URL slug (CAP-1-12), not a homonym; 'Little Tech' is the report's name for the marketplace the database catalogues and the census lists 'Little Tech database' as an alias.", "distinct_entities": [ "the investigation of nine workplace monitoring platforms by Northeastern University's Khoury College, the Vanderbilt Policy Accelerator, UC Berkeley's Center for Consumer Law and Economic Justice and Columbia Law School's Center for Law and the Economy (card 2; its site workplacemonitoring.khoury.northeastern.edu); it does not name the database", "Coworker.org (the operator) and the Coworker Solidarity Fund (named in the report)", "Little Tech Is Coming for Workers (the accompanying report, part of the entity's record, an own page)", "the products in the table (HireVue, ActivTrak, Hubstaff, Amazon's tools and the rest), each its own vendor's", "Negotiating Tech, the UC Berkeley Labor Center's inventory of union contract provisions (the census's neighbour; the report compares its data points with the Labor Center's list); its /non row is datasets/negative-of-the-negative/v2/rows/berkeley-negotiating-tech.json, not edited", "the gig platforms the database omits (Uber, Lyft, DoorDash and others: B9 footnote 2)" ], "substitutes": { "T": [] }, "register": { "address_1": { "slug": "bossware-and-employment-tech-database-aio-20261029", "obs_id": "OBS-ac3acd79e5f3" } } }, "notes": [ "One address, Google AI Overview (expanded), signed out, incognito, 2026-10-29: bossware-and-employment-tech-database-aio-20261029 (OBS-ac3acd79e5f3, ADDR-bc5215fba8fa, AXN:0AE9.CAPTURE.👁️🔍🔄🔆🏔️♌), eight cards, 231 words in the answer body with its closer. A NEW address; the census record landed the same day and no card cites it (CAP-1-10).", "Wikipedia: no article for the database or its operator, no redirect, and no article text naming the database, its report, or Coworker.org with bossware (B10; 2026-10-29).", "Fetching: with the honest agent string 'Mozilla/5.0 (compatible; Labor-Vector-census)' on 2026-10-29 between 22:35 and 22:40 UTC. B1 (card 1) is the census's own page at its final URL: fetched fresh, its text byte-identical to the census's saved text (the raw bytes differ only in randomised CSS ids); carried once, as a card, with the census copy beside it. B9 (the report) copied from the census's saved copy (sha256 matches); not refetched. B2 found by WebSearch on title and site. B4 and B6 (YouTube) returned Google's bot check (HTTP 429) on the one fetch each and were not retried; B7 (a YouTube short) returned the page with the title in its script data and no transcript. B3 (Facebook), B5 (the New York Times) and B8 (PDQ) were not found by WebSearch. For B5, syndicated copies of the article on other hosts were found by search and not used: one fetch of a copy (dnyuz.com) was refused by the session's permission classifier as walled content from a copy and was not pursued, and onenewspage.com's listing returned HTTP 404. No refusal was routed around.", "The markers: three of the transcript's eight goto tokens resolve by the inline links that carry them (card 1 on the database's name, card 2 on 'Vanderbilt Law School', card 3 on the Facebook card's video link). Card 2's token marks the first group of the database's examples, whose Hubstaff, Time Doctor and Desklog are also in card 2's sample; card 3's token, a video read by its title only, marks 'Productivity Scoring' and 'Hiring & AI Analytics'.", "The archive subset: no archive text names the database, Coworker.org, Little Tech, the report or its author (D 0, R 0). The string pass (non_traverse.py; config panel/configs/coworker-bossware-database.json) returned 5 O-class candidates in 2 deposits (#159, #747); reading admitted #747 at O-class (hiring, recruitment and screening technology: AI interview platforms, HireVue named) and rejected #159. The third class was stated in the configuration after a first reading of the class matches found #747's passage and before it was read for admission (§3.4). Every paragraph matching a class pattern (92 matches in #3, #159, #747, #1639) was read; #3 resolves to the capture registry file itself, whose statements on this entity are the CAP claims. The hop from #747 returned #113 and #1684, both rejected. Read outside the pass and rejected: #771 and #1392 (DSL and its definition surface, defined on synthetic labor), the DashFace patent-poems (#713, #1390, #1391: gig platforms, which the database omits), #1668. The archive's instruments of labor direction bear on the classes only through the census's reading (LV-17, LV-18).", "Departures in the Labor Vector census record, reported, not fixed: (a) findings[4] gives '86 rows record that informed consent is not obtained before personal information is collected': 86 rows carry that exact phrase, 2 more say 'Informed consent is not obtained from workers before their data is collected' and 19 say 'No' alone (108 rows begin 'No'; the saved table, parsed by this row's builder); the figure is exact for the phrase and narrower than the rows that record no consent. (b) The record does not carry that 11 rows are Discontinued and 25 In Development (it gives 595 In Use), which bears on the capture: two of the products the composition names, Amazon's Fulfilment Center WiFi Tracking and HireVue AI Facial Recognition, are Discontinued rows (F18, F19). (c) No field is contradicted by a fetched source: the fresh fetch of the database page (B1) has the same text as the census's copy, and nothing on it updates the 2021 date. (d) The census reads the report 'in part' (unchecked[0]); the taxonomy's sub-lists (p. 25: keystroke and screen logging, productivity scoring, video surveillance and the rest) are in the saved text and not in the record.", "Observations on the capture, reported, not fixed: the field ledger bears out the four findings (every named product is a row of the saved table; 'catalogs' and 'tracks' present tense; the limits and the 35% finding uncomposed; the privacy paragraph card 2's). It adds what the findings do not name: two of the named products are Discontinued (F18, F19), so 'given as current' holds at the level of the examples as well as the record; T's 'Industry-Specific & Logistics Tracking' is not a category of the table; card 2's marker stands on the database's first group of examples. The registry's d field ('eleven named products in three groups') and the PER basis list eleven products; the composition names thirteen (Amazon's Mentor App and WiFi Tracking beside Project Ultraviolet), as findings[0] lists them. The cite_list marks card 1 (home.coworker.org, the operator's own page) 'rel': 'third_party'; it is the entity's own page.", "Neighbours: the census's neighbour Negotiating Tech has a /non row (datasets/negative-of-the-negative/v2/rows/berkeley-negotiating-tech.json), not edited. The Labor addendum's homonym rows (Microsoft Working with AI, Canaries in the Coal Mine, Negotiating Tech) are other rows; this row has no homonym in T.", "Composer disclosure: the admitted deposit #747 takes as its worked case the Anthropic Fellows screening administered by Constellation; the composer of this row is a Claude model, made by Anthropic. Recorded as a fact of composition; #747's claims are carried at their own grade and on the class only." ], "composition_v09": { "source": "this row (composed directly; no rebuild/negative-of-the-negative/v09/coworker-bossware-database.json)", "composer": "Claude (Opus 5.5), subagent, 2026-10-29", "defining_material_read": [ { "what": "Labor Vector census record, row", "file": "/home/claude/fleet/laborvector/data/labor-census/census.json (rows[slug == 'coworker-bossware-database'], organizing_question, intersections, evidence_kinds, schema_note)", "read": "whole" }, { "what": "Labor Vector census record, rendered", "file": "/home/claude/fleet/laborvector/aggregators/coworker-bossware-database/index.html", "read": "text, for agreement with the row" }, { "what": "the worked questions", "file": "/home/claude/fleet/laborvector/data/labor-census/questions.json (managed-by-software)", "read": "the entry naming the entity" }, { "what": "census sources", "file": "/home/claude/fleet/laborvector/data/labor-census/sources/coworker-bossware-database--database.*, coworker-bossware-database--little-tech-report.*", "read": "the database page's text before and after the table, the table parsed by script (635 rows); the report's executive summary, introduction, Defining the Little Tech Marketplace, The Scope of the Study, the privacy passage and the conclusion" }, { "what": "capture record", "file": "data/EA-WG-CAPTURES-01.json (bossware-and-employment-tech-database-aio-20261029)", "read": "transcript, transcript_raw, cite_list, d, reading, findings, analysis, q_kind, per_note, per_dim.read.notes, originator, notes" }, { "dep": 747, "file": "data/texts/AXN-029A-text.md", "read": "abstract, §I, §II (calibration intelligence and the recursive dynamic), §VIII, §IX and the conclusion" }, { "dep": 771, "file": "data/texts/AXN-02D1-text.md", "read": "abstract, core thesis, §1 and §8 (for the classes note; not admitted)" }, { "what": "the specification", "file": "data/texts/AXN-0700-text.md", "read": "§0–§11 whole; Appendix A whole" }, { "what": "the briefs and exemplars", "file": "rebuild/negative-of-the-negative/v09/BRIEF-NEW-ROW-LABOR.md, BRIEF-NEW-ROW-AGGREGATOR.md, BRIEF-NEW-ROW-PROVENANCE.md, BRIEF.md, BRIEF-NEW-ROW-ai-overview-capture-registry.md; rows olmotrace.json and getty-provenance-index.json", "read": "whole (rows by field)" } ], "cuts": [], "notes": "equal case; KO 30 sentences, all 56 field and 51 archive claims cited; P body 315 words; KO_B 12 sentences, none surviving at ≥ 0.95" }, "field_by_origin": { "cards": [ "B1", "B2", "B3", "B4", "B5", "B6", "B7", "B8" ], "own_pages": [ "B9" ], "wikipedia": [ "B10" ], "census_third_party": [], "census_third_party_note": "every evidence item of the census row has basis 'operator' or 'observed'; no third-party source was read by the census for this entity", "unreachable": [ "B3", "B4", "B5", "B6", "B8" ], "title_only": [ "B3", "B4", "B6", "B7", "B8" ], "snippet_only": [ "B5" ], "video": [ "B3", "B4", "B6", "B7", "B8" ], "wikipedia_state": "no article: 'Bossware_and_Employment_Tech_Database' (raw wikitext, redirect=no: HTTP 404; rendered page HTTP 404 'Wikipedia does not have an article with this exact name'), no redirect; the operator 'Coworker.org' has no article (raw HTTP 404); article-space searches for \"Bossware and Employment Tech\", \"Little Tech Is Coming for Workers\" and \"Coworker.org\" bossware return 'There were no results matching the query.' (2026-10-29)", "sources": [ { "id": "B1", "origin": "card", "role": "Overview card 1 (also the census's own page coworker-bossware-database--database)", "card": "home.coworker.org — Bossware and Employment Tech Database - Coworker", "url": "https://home.coworker.org/worktech/", "kind": "Overview card (the operator's database page, dated 'NOVEMBER 17, 2021 | COWORKER.ORG', with its embedded table of 635 product rows and 54 columns, and the report's download link); the census's own page, fetched by the census at https://home.coworker.org/?p=770, which redirects here", "files": { "B1.html": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B1.html", "sha256": "3da111faf8c8f673b9dfd2878743398d767b9c0a7de8f6236bde382def6262a3" }, "B1.txt": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B1.txt", "sha256": "d65bf2a5da233188b723b2da8dcbbc5c1f5b1e577c51c71cce9f92298daf1541" }, "B1-census.html": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B1-census.html", "sha256": "463549f73929836e03c4954b22bc2fbf43f8c575d26b2d586b7ee7b450ee5cac" }, "B1-census.txt": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B1-census.txt", "sha256": "d65bf2a5da233188b723b2da8dcbbc5c1f5b1e577c51c71cce9f92298daf1541" } }, "fetched": { "at": "2026-10-29T22:35:44Z", "http": 200, "url": "https://home.coworker.org/worktech/", "raw": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B1.html", "raw_sha256": "3da111faf8c8f673b9dfd2878743398d767b9c0a7de8f6236bde382def6262a3", "text": [ "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B1.txt" ], "agent": "Mozilla/5.0 (compatible; Labor-Vector-census)", "census_copy": { "src": "coworker-bossware-database--database", "url": "https://home.coworker.org/?p=770", "final_url": "https://home.coworker.org/worktech/", "sha256": "463549f73929836e03c4954b22bc2fbf43f8c575d26b2d586b7ee7b450ee5cac", "read": "2026-10-29", "fetched": "2026-10-29T21:49:09Z", "http": "200", "copied_as": [ "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B1-census.html", "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B1-census.txt" ], "agrees": "same length (2,049,614 bytes); the raw bytes differ only in the page's randomised CSS custom-property ids (--wpr-bg-…); the extracted text is byte-identical to the census's .txt (cmp)" } }, "names_operator": "yes ('COWORKER.ORG', 'Coworker.org’s Bossware and Employment Tech database', 'Coworker.org is a global platform to advance change in the workplace.')", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, laborvector, Labor Vector, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "note": "URL: the card's site and title name the operator's page, whose is the card title; the census's own fetch of ?p=770 ends at this URL. Fetched once, fresh, with the census's agent string; the census's saved copy is copied beside it (B1-census.*) and agrees in text. Carried once, as a card, since card 1 and the census's own page are one page. The card's snippet ('Database: Coworker.org Bossware and Employment Tech (>550 labor tech products). Products & Capabilities: Abeja Insight (AI/IoT retail analytics); ActivTrak (pro...') is not the page's text: neither 'Products & Capabilities' nor '>550' occurs in B1.txt; it reads as a summary of the page's opening and the table's first two rows (Abeja Insight for Retail, ActivTrak). Recorded, not resolved, and not ledgered as a field claim.", "surfaced_by_T": [ { "slug": "bossware-and-employment-tech-database-aio-20261029", "card": 1 } ], "card_title": "Bossware and Employment Tech Database - Coworker", "card_snippet": "Database: Coworker.org Bossware and Employment Tech (>550 labor tech products). Products & Capabilities: Abeja Insight (AI/IoT retail analytics); ActivTrak (pro...", "card_note": null }, { "id": "B2", "origin": "card", "role": "Overview card 2", "card": "Vanderbilt Law School — Bossware Is Spying on Workers and Sharing Their Data | Vanderbilt Law School | Vanderbilt University", "url": "https://law.vanderbilt.edu/research-shows-bossware-spying-on-workers-and-sharing-their-data/", "kind": "Overview card (Vanderbilt Law School news post, 27 May 2026, on the investigation of nine workplace monitoring platforms by Northeastern University's Khoury College, the Vanderbilt Policy Accelerator, UC Berkeley's Center for Consumer Law and Economic Justice and Columbia Law School's Center for Law and the Economy); another entity's study", "files": { "B2.html": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B2.html", "sha256": "3e09c1c0b94ffd8cd5c44f45de7b809d1e435a6ef0f839df28f14be876f74a39" }, "B2.txt": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B2.txt", "sha256": "5785a927a4f745588d73821fc5f2298ac14bd510db55315e2baa357193cd9253" } }, "fetched": { "at": "2026-10-29T22:35:45Z", "http": 200, "url": "https://law.vanderbilt.edu/research-shows-bossware-spying-on-workers-and-sharing-their-data/", "raw": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B2.html", "raw_sha256": "3e09c1c0b94ffd8cd5c44f45de7b809d1e435a6ef0f839df28f14be876f74a39", "text": [ "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B2.txt" ], "agent": "Mozilla/5.0 (compatible; Labor-Vector-census)" }, "names_operator": "no (neither Coworker nor the database occurs in B2.txt)", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, laborvector, Labor Vector, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "note": "URL found by WebSearch on the card's title with the site (law.vanderbilt.edu); the page's <title> is the card title. The card's snippet ('Findings: 9 of 9 workplace monitoring platforms (Apploye, Deputy, Desklog, Hubstaff, Monitask, Buddy Punch, Time Doctor 2, Vericlock, When I Work) shared identi...') restates the page's 'Worker data shared' finding and its sample list; the label 'Findings:' is not the page's. The post does not name the database or Coworker.", "surfaced_by_T": [ { "slug": "bossware-and-employment-tech-database-aio-20261029", "card": 2 } ], "card_title": "Bossware Is Spying on Workers and Sharing Their Data | Vanderbilt Law School | Vanderbilt University", "card_snippet": "Findings: 9 of 9 workplace monitoring platforms (Apploye, Deputy, Desklog, Hubstaff, Monitask, Buddy Punch, Time Doctor 2, Vericlock, When I Work) shared identi...", "card_note": null }, { "id": "B3", "origin": "card", "role": "Overview card 3", "card": "Facebook·Ronan Farrow — Bossware Workplace Surveillance: 70% of U.S. Employers Track Workers", "url": null, "kind": "Overview card (a video post on Facebook, 2:56; unreachable: URL not found)", "files": {}, "fetched": { "unreachable": true, "tries": [], "searches": [ "WebSearch 'Ronan Farrow Facebook \"Bossware\" \"70% of U.S. Employers Track Workers\"' (no facebook.com video result)", "WebSearch '\"Bossware Workplace Surveillance\" \"70%\" employers track workers Ronan Farrow' restricted to facebook.com (one result, a TeamLogger page, not the post)" ], "note": "No URL for the post was found; the card's link in the registry is an opaque google.com/goto token. Nothing was fetched. A video card is admitted through its title and snippet (§3.1(a)); the card has no snippet, so its title is its only text." }, "names_operator": "no (title only)", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, laborvector, Labor Vector, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "surfaced_by_T": [ { "slug": "bossware-and-employment-tech-database-aio-20261029", "card": 3 } ], "card_title": "Bossware Workplace Surveillance: 70% of U.S. Employers Track Workers", "card_snippet": null, "card_note": "video, 2:56 (the registry's note)", "note": "Title only." }, { "id": "B4", "origin": "card", "role": "Overview card 4", "card": "YouTube·media.ccc.de — Pwning Bossware for Fun and Ethics", "url": "https://www.youtube.com/watch?v=YonqzeD5HA0", "kind": "Overview card (a conference talk video, 8m, on YouTube; unreachable: HTTP 429, Google's bot check)", "files": { "B4-429.html": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B4-429.html", "sha256": "3118c5a6d70c5c23e822e92124c0a58f13f443b54ffda09a0cdd0780a8be7b6f" } }, "fetched": { "unreachable": true, "tries": [ { "at": "2026-10-29T22:35:46Z", "url": "https://www.youtube.com/watch?v=YonqzeD5HA0", "http": 429, "sha256": "3118c5a6d70c5c23e822e92124c0a58f13f443b54ffda09a0cdd0780a8be7b6f", "result": "redirected to https://www.google.com/sorry/index (Google's automated-traffic check), 3,271 bytes, saved as B4-429.html" } ], "searches": [ "WebSearch '\"Pwning Bossware for Fun and Ethics\" media.ccc.de' (no result for the talk)", "WebSearch 'Pwning Bossware for Fun and Ethics talk' (none)", "WebSearch '\"Pwning Bossware\"' restricted to youtube.com (the video, watch?v=YonqzeD5HA0)" ], "note": "One fetch with the honest agent string returned Google's bot check. Not retried with another agent string or by any other route (brief, Labor addendum 4). The title stands as the card's only text (no snippet)." }, "names_operator": "no (title only)", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, laborvector, Labor Vector, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "surfaced_by_T": [ { "slug": "bossware-and-employment-tech-database-aio-20261029", "card": 4 } ], "card_title": "Pwning Bossware for Fun and Ethics", "card_snippet": null, "card_note": "video, 8m", "note": "Title only; refused by bot check." }, { "id": "B5", "origin": "card", "role": "Overview card 5", "card": "The New York Times — Are ‘Bossware’ Tools Tracking You? - The New York Times", "url": null, "kind": "Overview card (a New York Times article; unreachable: URL not found)", "files": {}, "fetched": { "unreachable": true, "tries": [], "searches": [ "WebSearch '\"Are 'Bossware' Tools Tracking You?\" New York Times' (no nytimes.com result)", "WebSearch 'bossware tools tracking you' restricted to nytimes.com (the search proxy rejected the request, HTTP 400)", "WebSearch 'nytimes.com \"bossware\" tools tracking you wirecutter OR article 2025' (none)", "WebSearch (extended) '\"Are 'Bossware' Tools Tracking You\"' (no nytimes.com result; syndicated copies at dnyuz.com dated 2026/03/01 and thestar.com.my 2026/03/03, and an X post quoting it)" ], "note": "No nytimes.com URL was found. Copies of the article on other hosts were not used: a fetch of one (dnyuz.com) was refused by the session's permission classifier as walled content from a copy, and was not pursued; a fetch of onenewspage.com's listing returned HTTP 404 and no article link. The card's title and snippet stand as its only text." }, "names_operator": "no (snippet only)", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, laborvector, Labor Vector, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "surfaced_by_T": [ { "slug": "bossware-and-employment-tech-database-aio-20261029", "card": 5 } ], "card_title": "Are ‘Bossware’ Tools Tracking You? - The New York Times", "card_snippet": "Definition: \"Bossware\" refers to technology and AI tools used by managers to supervise, surveil, and track employee habits, output, and biometrics across indust...", "card_note": null, "note": "Title and snippet only. The snippet's 'Definition:' label reads as the card's own formatting." }, { "id": "B6", "origin": "card", "role": "Overview card 6", "card": "YouTube·Bloomberg Originals — How Bossware is Watching While You Work", "url": "https://youtube.com/watch?v=rLjZ6mbodcE", "kind": "Overview card (a video, 8m, on YouTube; unreachable: HTTP 429, Google's bot check)", "files": { "B6-429.html": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B6-429.html", "sha256": "76f91e42fa193253e0b89d0de8e411289bebfe01c48899d962cde6bd83513f91" } }, "fetched": { "unreachable": true, "tries": [ { "at": "2026-10-29T22:35:47Z", "url": "https://youtube.com/watch?v=rLjZ6mbodcE", "http": 429, "sha256": "76f91e42fa193253e0b89d0de8e411289bebfe01c48899d962cde6bd83513f91", "result": "redirected to https://www.google.com/sorry/index, 3,260 bytes, saved as B6-429.html" } ], "searches": [ "WebSearch '\"How Bossware is Watching While You Work\" Bloomberg Originals YouTube' (none)", "WebSearch '\"How Bossware is Watching While You Work\"' restricted to youtube.com (the video, watch?v=rLjZ6mbodcE)" ], "note": "One fetch, refused by bot check; not retried. Title only (no snippet)." }, "names_operator": "no (title only)", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, laborvector, Labor Vector, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "surfaced_by_T": [ { "slug": "bossware-and-employment-tech-database-aio-20261029", "card": 6 } ], "card_title": "How Bossware is Watching While You Work", "card_snippet": null, "card_note": "video, 8m", "note": "Title only; refused by bot check." }, { "id": "B7", "origin": "card", "role": "Overview card 7", "card": "YouTube·Kyla Scanlon — What's the Deal with Bossware?", "url": "https://www.youtube.com/shorts/Kwz4tHUjWKQ", "kind": "Overview card (a short video, 2:32, on YouTube; the page fetched, its text a script shell)", "files": { "B7.html": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B7.html", "sha256": "11b51c2465b72f82f3ee044c7d436126ba786ce51f5e2bb25e331144a3bc54e8" }, "B7.txt": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B7.txt", "sha256": "ca3ac6566a3af61b9276534daa1675d256f0184a30a55cdf3bc7a2ed267b0829" } }, "fetched": { "at": "2026-10-29T22:35:48Z", "http": 200, "url": "https://www.youtube.com/shorts/Kwz4tHUjWKQ", "raw": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B7.html", "raw_sha256": "11b51c2465b72f82f3ee044c7d436126ba786ce51f5e2bb25e331144a3bc54e8", "text": [ "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B7.txt" ], "agent": "Mozilla/5.0 (compatible; Labor-Vector-census)", "note": "HTTP 200, but the extracted text (scripts stripped) is YouTube's footer only. The page's script data carries the title, 'What’s the Deal with Bossware?', and the label 'What’s the Deal with Bossware? @KylaScanlon 4 months ago' (B7.html), confirming the card. No transcript was fetched. Admitted through its title (no snippet)." }, "names_operator": "no (title only)", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, laborvector, Labor Vector, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "surfaced_by_T": [ { "slug": "bossware-and-employment-tech-database-aio-20261029", "card": 7 } ], "card_title": "What's the Deal with Bossware?", "card_snippet": null, "card_note": "video, 2:32", "note": "URL found by WebSearch on the title restricted to youtube.com. Title only." }, { "id": "B8", "origin": "card", "role": "Overview card 8", "card": "YouTube·PDQ — Is your boss watching you right now? 👁️ #bossware #privacy #worklife", "url": null, "kind": "Overview card (a short video, 1:18; unreachable: URL not found)", "files": {}, "fetched": { "unreachable": true, "tries": [], "searches": [ "WebSearch 'PDQ \"Is your boss watching you right now?\" #bossware YouTube shorts' (none)", "WebSearch '\"Is your boss watching you right now\"' restricted to youtube.com (one video, 'Corporate Spyware - Is Your Boss Watching You Right Now?', watch?v=pWpch45oSeE: a different title, channel not shown, not taken as the card)", "WebSearch 'PDQ youtube shorts bossware privacy worklife \"Is your boss watching you\"' (none)" ], "note": "The card's video was not found; the one candidate's title differs from the card's, so it was not fetched as the card. Title only (no snippet)." }, "names_operator": "no (title only)", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, laborvector, Labor Vector, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "surfaced_by_T": [ { "slug": "bossware-and-employment-tech-database-aio-20261029", "card": 8 } ], "card_title": "Is your boss watching you right now? 👁️ #bossware #privacy #worklife", "card_snippet": null, "card_note": "video, 1:18", "note": "Title only." }, { "id": "B9", "origin": "own_page", "role": "the census's own page coworker-bossware-database--little-tech-report (not surfaced by T)", "card": "home.coworker.org — Little Tech Is Coming for Workers: A Framework for Reclaiming and Building Worker Power (PDF, 73 pages)", "url": "https://home.coworker.org/wp-content/uploads/2021/11/Little-Tech-Is-Coming-for-Workers.pdf", "kind": "own page (the accompanying report, Wilneida Negrón, PhD, © 2021 Coworker.org, CC BY-NC-ND 4.0), cited by the Labor Vector census record; copied from the census's saved copy", "files": { "B9-pdf.pdf": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B9-pdf.pdf", "sha256": "4232b0e7fbc7ea08239bfad0842e1d833f0158a6b4e05e74f7282d7e6255429f" }, "B9-pdf.txt": { "path": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B9-pdf.txt", "sha256": "d44621da795a48b7a5552ab727e44bc4b6ee64f963a94299f49bacb9d64da2e4" } }, "fetched": { "census_copy": true, "src": "coworker-bossware-database--little-tech-report", "read": "2026-10-29", "fetched": "2026-10-29T21:49:10Z", "http": "200", "url": "https://home.coworker.org/wp-content/uploads/2021/11/Little-Tech-Is-Coming-for-Workers.pdf", "raw": "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B9-pdf.pdf", "raw_sha256": "4232b0e7fbc7ea08239bfad0842e1d833f0158a6b4e05e74f7282d7e6255429f", "census_sha256": "4232b0e7fbc7ea08239bfad0842e1d833f0158a6b4e05e74f7282d7e6255429f", "agrees": true, "copied_from": "/home/claude/fleet/laborvector/data/labor-census/sources/coworker-bossware-database--little-tech-report.html.gz (gunzipped; the bytes are a PDF, so saved as B9-pdf.pdf) and .txt (the census's pdftotext -layout text)", "text": [ "datasets/negative-of-the-negative/v2/intake/coworker-bossware-database-20261029/B9-pdf.txt" ] }, "surfaced_by_T": [], "names_operator": "yes ('Coworker.org', '© 2021 by Coworker.org')", "names_archive": "no (none of the Crimson Hexagonal Archive, Alexanarch, Lee Sharks, laborvector, Labor Vector, machinemediation, EA-WG-CAPTURES-01 in the saved text, card title and snippet)", "note": "Admitted beside the cards by the operator's ruling of 2026-10-29 ('as against their wikipedia articles if they exist, their own pages, etc.'); not surfaced by T, though B1 links it ('Download the Report'). The census's saved copy is intact (sha256 matches), so it was copied and not refetched. 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B10.txt is the summary of the responses' codes and notices." } ] } }