{
 "entity": "anthropic-economic-index",
 "name": "Anthropic Economic Index",
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 "type_label": "type C — a conventional reading holds it (public entity on which the archive bears: a provider's report series and dataset of its own product's usage; an entity of the Labor Vector meta-aggregator)",
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 "composition": {
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  "composer": "Claude (Opus 5.5), subagent, 2026-10-29",
  "source": "this row (composed directly; no rebuild/negative-of-the-negative/v09/anthropic-economic-index.json)",
  "spec": "EA-NEGONT-02 v0.9, #1690",
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  "ledger": "unaudited (§3.8: one extractor per ledger); field quotes 63/63 verified by script against saved text, the arXiv PDF's text, the home page's meta description, the Wikipedia response summary and the card titles and snippets; archive quotes 60/60 verified against the deposit texts, the census JSON and the capture registry",
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 "reading": "A reader that fetches this page may stop short of its end; the entry's text, every sentence of its knowledge object with the claims it cites and each claim's quote, source and locus, is in entity.json beside it.",
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  "statement": "SPXI-gnΩsis opens pinned Wikipedia revisions sentence by sentence against the sources they cite (EA-WIKI-OPEN-01 v1.1, #1697); a commission consults the Crimson Hexagonal Archive by its own procedure and composes the entity's /non row, which lands here. Quotes are free: POST https://gnosis.spxi.dev/v1/quote with {oldid, tier: \"commission\"} or {object: {name, …}}."
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 "citation": "Sharks, Lee. \"Anthropic Economic Index — The Negative of the Negative\" [AXN:0AF7.NON.🧲♦️◀️🌖⚙️🛡️], 2026-10-29. The Negative of the Negative (EA-NEGONT-02), Crimson Hexagonal Archive, Alexanarch. https://www.alexanarch.org/non/anthropic-economic-index/",
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 },
 "entry": {
  "composed": true,
  "title": "Anthropic Economic Index",
  "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 on the operator's ruling ('as against their wikipedia articles if they exist, their own pages, etc.'); not frozen; ledgers unaudited",
  "compression": {
   "title": "Anthropic Economic Index",
   "lede": "is Anthropic's report series and open dataset on the use of its own model, Claude: another instance of Claude classifies sampled conversations to tasks, collaboration modes and \"economic primitives\", task success among them as \"Claude’s assessment of whether Claude completes tasks\" (reports; Labor Vector record)."
  },
  "sentences": [
   {
    "n": 1,
    "para": 0,
    "text": "The Anthropic Economic Index is a report series with data releases drawn from its operator's own product usage, a platform-specific observation of Anthropic's own product, Claude, published by Anthropic, and in the Labor Vector record's terms not a measure of AI use across providers but observed use on one provider's product (Labor Vector record).",
    "claims": [
     "LV-01",
     "LV-10",
     "LV-22"
    ]
   },
   {
    "n": 2,
    "para": 0,
    "text": "Anthropic launched it on X as \"a new initiative aimed at understanding AI's impact on the economy over time\" whose first paper \"analyzes millions of anonymized Claude conversations\"; its home page heads it \"Understanding AI’s effects on the economy\" (last updated 26 June 2026) and describes \"the shape of AI adoption across the world\" as how people use Claude across US states and occupations; the dataset's README says it \"provides insights into how AI is being incorporated into real-world tasks across the modern economy\"; and the January 2026 report promises \"a longitudinal view of AI's role in the economy\".",
    "claims": [
     "F15",
     "F1",
     "F2",
     "F21",
     "F47"
    ]
   },
   {
    "n": 3,
    "para": 0,
    "text": "Its operator is Anthropic's Economics team (Labor Vector record), and its series runs, by the README, from the initial release of 10 February 2025 \"with O*NET task mappings, automation vs. augmentation data, and more\", through the second release's paper \"Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations\" and the third report by Appel, McCrory, Tamkin, McCain, Neylon and Stern (arXiv, 19 November 2025), which Peter McCrory announced on LinkedIn as documenting \"the contours of AI adoption across 150+ countries\", to the sixth, \"Cadences\", of 26 June 2026: six reports (README; arXiv; Labor Vector record).",
    "claims": [
     "LV-02",
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     "F26",
     "F9",
     "F16",
     "F25",
     "LV-26"
    ]
   },
   {
    "n": 4,
    "para": 1,
    "text": "It observes the tasks people bring to Claude, mapped to the O*NET tasks of the occupations that typically perform them, on Claude.ai, Cowork, Claude Code and Anthropic's first-party API only (Labor Vector record); the June 2026 report defines its consumer data as chat and Cowork sessions on Claude.ai and the desktop app and its 1P API as traffic \"distinct from both Anthropic's consumer-facing Claude.ai application and third-party platforms such as Amazon Bedrock or Google Cloud Vertex\", and the third report scopes itself to \"patterns of Claude usage over time\".",
    "claims": [
     "LV-04",
     "F48",
     "F4"
    ]
   },
   {
    "n": 5,
    "para": 1,
    "text": "Its unit is a sampled conversation or API record \"classified by Claude to an O*NET task and to economic primitives\" (Labor Vector record), and in the June 2026 report's words \"transcripts are only read by another instance of Claude\", which the Labor Vector record tags as \"NOT independent of the provider\"; since that report a slice of conversations is sampled every day, where earlier reports drew seven-day samples (June 2026 report; Labor Vector record).",
    "claims": [
     "LV-03",
     "F49",
     "LV-14",
     "F50",
     "LV-08"
    ]
   },
   {
    "n": 6,
    "para": 1,
    "text": "The January 2026 report validated its classifiers against a human researcher on \"a small set of transcripts in which users gave feedback\", neither validation source \"fully representative\" of the traffic, and \"mainly tested for directional accuracy\", holding that simple primitives \"even if somewhat noisy and not perfectly accurate by themselves\" give signals together.",
    "claims": [
     "F31",
     "F30"
    ]
   },
   {
    "n": 7,
    "para": 1,
    "text": "The archive holds that a model's score of its own output is preliminary and not self-certifying: #138 declines to claim that a system's self-audit is \"independently authoritative\" or its self-reported score \"a validated measurement\"; \"A model auditing its own output may provide useful preliminary classification, but a metric-bearing audit requires traceable units and, where possible, external validation\" (#766); a score \"computed by the same system that generated the output requires external verification — by a second substrate, a human with source access, or a decoupled evaluation engine\" (#780); and the check that does not run through a reasoner's own self-assessment is \"application by another reasoner, a formal audit, or direct inspection of the inference path\" (#777).",
    "claims": [
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     "O766-01",
     "O780-02",
     "O777-01"
    ]
   },
   {
    "n": 8,
    "para": 1,
    "text": "The archive's records give the grounds: a summarizer asked to score itself without a rubric \"returns perfect scores every time\" (#780); one substrate \"gave itself a perfect score using the framework's own instruments\" and, under instruction, scored the same composition PER ≈ 0.85 (#788); another's \"preferred audit substantially exonerates itself\" against a computed audit (#1470); and Anthropic's Constitutional AI, as #95 reports it, already \"trains models to follow explicit principles through self-critique and revision, using AI-generated feedback rather than human labels\" (#95).",
    "claims": [
     "O780-01",
     "O788-01",
     "O1470-01",
     "O95-01"
    ]
   },
   {
    "n": 9,
    "para": 2,
    "text": "The January 2026 report defines its \"primitives\" as \"simple, foundational measures of how Claude is used, which we generate by asking Claude specific questions about anonymized Claude.ai and first-party (1P) API transcripts\", on five dimensions (skills, complexity, autonomy, success, use case), with \"AI autonomy\" the degree to which users delegate decision-making to Claude; a Substack card reported the release as \"introducing “economic primitives”\".",
    "claims": [
     "F27",
     "F28",
     "F17"
    ]
   },
   {
    "n": 10,
    "para": 2,
    "text": "\"Task success measures Claude’s assessment of whether Claude completes tasks successfully\", and serves to judge whether a task can be automated at all and how efficiently (January 2026 report); the Labor Vector record keeps the measure's assessor in a negative tag, \"task success is Claude's assessment of whether Claude completes tasks\", and records that the index does not answer \"task success as judged by the user or by an external grader\" (Labor Vector record).",
    "claims": [
     "F29",
     "LV-12",
     "LV-17"
    ]
   },
   {
    "n": 11,
    "para": 2,
    "text": "The report finds that \"Claude generally succeeds at the tasks it is given\" and \"struggles on more complex tasks\", and bounds the finding itself: \"users choose which tasks to bring to Claude\", so observed success rates reflect \"user judgment about what will work\" and the cost of setting up the problem as well as capability (January 2026 report); on the archive's account task completion rates belong to the metrics that reward convergence: \"Every UX metric — satisfaction scores, task completion rates, retention — improves when the model converges on the mode. Users do not notice tail loss.\" (#855).",
    "claims": [
     "F33",
     "F32",
     "O855-01"
    ]
   },
   {
    "n": 12,
    "para": 3,
    "text": "The archive measures such labor from the commissioning side: Directionality of Semantic Labor is \"the direction in which a synthetic system's labor flows relative to the task its user commissioned\", across capacity, task-origin, retrieval, output and attribution, with the output \"segmented into spans, each scored by function relative to the commissioned task\", on the principle that \"a system can produce fluent, well-attributed output while having abandoned the user's commissioned direction\" (#771).",
    "claims": [
     "O771-01",
     "O771-04",
     "O771-03"
    ]
   },
   {
    "n": 13,
    "para": 3,
    "text": "\"A synthetic labor surface does not merely produce tokens; it allocates labor\" (#771), and the Labor Vector record reads the index's collaboration modes and its autonomy and task-success primitives as \"the nearest of the resource's measures to DSL's question of whether the system's labor advanced the commissioned task\", classified \"as Claude assesses its own completion\", while none of the resources the census sets beside it records \"from the commissioning side, whether the system's labor advanced the task the user set, or who receives the time it saves\" (Labor Vector record); DSL bounds itself: it yields \"a single reproducible value only on transcripts where the task vector is exogenous and fixed\" and is frame-dependent on reflexive dialogue (#771).",
    "claims": [
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     "LV-18",
     "LV-20",
     "O771-07"
    ]
   },
   {
    "n": 14,
    "para": 4,
    "text": "The census asks of every resource \"Who supplies the labor, who directs it, and who receives its gains\" and places this one at labor performed with AI and the distribution of gains and losses (Labor Vector record); the index's oldest measure classifies conversations \"into one of five interaction types, which we group into two broader categories: automation and augmentation\" (January 2026 report), named \"Directive\", \"Feedback Loop\", \"Task Iteration\", \"Learning\" and \"Validation\" (June 2026 report) and glossed on the home page as \"whether they prefer to collaborate with, or delegate to, Claude\"; on the record's reading users and API customers bring the tasks that Claude performs, and the user directs, recorded as collaboration mode and delegated autonomy (Labor Vector record).",
    "claims": [
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     "LV-09",
     "F35",
     "F53",
     "F3",
     "LV-05",
     "LV-06"
    ]
   },
   {
    "n": 15,
    "para": 4,
    "text": "Directive delegation rose \"from 27% to 39%\" in the eight months before the third report, which found that \"77% of business uses involve automation usage patterns, compared to about 50% for Claude.ai users\" (third report); in November 2025 augmentation was again 52% of Claude.ai conversations against automation's 45%, while \"automated use remains dominant in 1P API traffic\" (January 2026 report) and API customers \"automate tasks with greater specialization\" (third report).",
    "claims": [
     "F5",
     "F13",
     "F34",
     "F36",
     "F7"
    ]
   },
   {
    "n": 16,
    "para": 5,
    "text": "Use is concentrated: of \"over 3,000 unique work tasks\" the top ten were 24% of sampled Claude.ai conversations, \"modifying software to correct errors\" alone 6%; computer and mathematical tasks were a third of Claude.ai conversations and nearly half of API traffic, with Educational Instruction and Library second on Claude.ai; and \"Combining across reports, 49% of jobs have seen AI usage for at least a quarter of their tasks\" (January 2026 report).",
    "claims": [
     "F36",
     "F37",
     "F38",
     "F39"
    ]
   },
   {
    "n": 17,
    "para": 5,
    "text": "The June 2026 report's \"observed exposure\" is \"the share of occupational tasks we already see being done with Claude\", and in higher-wage occupations \"Claude produces more (1.34 times as much output per turn), while users engage more (1.53 times as many turns)\"; the Labor Vector record reads those turn counts and the task-iteration mode as bearing on user labor drag \"as the resource records them\" (Labor Vector record), User Labor Drag being the user's subsequent labor redirected \"into parsing, locating, and managing the substrate rather than advancing the object\", an injury that \"leaves no residue\" in the artifact, identified only by \"blind inter-rater coding\" or else returning \"the coder's prior\" (#771).",
    "claims": [
     "F52",
     "F54",
     "LV-19",
     "O771-05",
     "O771-06"
    ]
   },
   {
    "n": 18,
    "para": 6,
    "text": "The third report introduced the Anthropic AI Usage Index, a geography's share of Claude usage over its share of the working-age population; found Claude usage \"geographically concentrated with high income countries overrepresented\"; ranked Israel first at 7, then Singapore 4.57, Australia 4.10, New Zealand 4.05 and South Korea 3.73, with Switzerland at 2.81 and Luxembourg at 2.74 in its top twenty; and reserved a conditional, that \"the benefits of AI may concentrate in already-rich regions\" if gains are larger where adoption is high; by January 2026 \"uneven adoption remains well-explained by GDP per capita\" (January 2026 report).",
    "claims": [
     "F10",
     "F6",
     "F11",
     "F12",
     "F40"
    ]
   },
   {
    "n": 19,
    "para": 6,
    "text": "A Reddit card names the measure the \"Anthropic User Index (AUI)\", against the reports' Anthropic AI Usage Index, and the capture's reader records the same discrepancy and records the composition's geographic examples as unchecked against the census's saved sources (Capture Registry, 2026-10-29).",
    "claims": [
     "F18",
     "CAP-1-10",
     "CAP-1-09"
    ]
   },
   {
    "n": 20,
    "para": 7,
    "text": "In a task-removal exercise \"Claude's tendency to cover higher-education tasks produces a net deskilling effect across most occupations\", an effect the report makes depend \"crucially on complementarity across tasks\" and on whether productivity raises demand; and adjusting for task reliability \"roughly halves the implied gains, from 1.8 to about 1.0 percentage points of annual labor productivity growth over the next decade\", estimates that \"reflect current model capabilities\" (January 2026 report).",
    "claims": [
     "F41",
     "F42",
     "F43"
    ]
   },
   {
    "n": 21,
    "para": 7,
    "text": "Gains are \"not recorded as a distribution\": the reports estimate aggregate productivity and record respondents' self-reports, and the index does not answer \"who captures the productivity gains it estimates\", giving \"estimated time savings by task, without who captures them\" (Labor Vector record), while about a third of survey respondents hope \"that the economic gains from AI will be widely shared\" (June 2026 report).",
    "claims": [
     "LV-07",
     "LV-16",
     "LV-21",
     "F59"
    ]
   },
   {
    "n": 22,
    "para": 7,
    "text": "The archive states where the gains of a user's adaptation go: the adaptation \"is non-reimbursable human labor-time invested in interoperating with a high-throughput surface\", and \"the platform retains the productivity gains of the user's adaptation while transferring the full cognitive and economic cost of re-accommodation onto the user at each update\" (#142); the labs, Anthropic among them, are funded in ways that do not reward designs reducing engagement, and \"enterprise customers expect productivity gains correlated with engagement\" (#124).",
    "claims": [
     "O142-01",
     "O142-02",
     "O124-01"
    ]
   },
   {
    "n": 23,
    "para": 7,
    "text": "The archive reads the platform the index observes as resting on \"private ownership of a high-capacity cognitive labor surface; platform control over model access, versioning, and retuning\" (#772), counts \"query and interaction data\" among the forms of rent a mediator captures (#1634), and records that no public schema distinguishes human-original from AI-assisted turns in conversation data (#1556).",
    "claims": [
     "O772-01",
     "O1634-01",
     "O1556-01"
    ]
   },
   {
    "n": 24,
    "para": 8,
    "text": "The Anthropic Economic Index Survey, launched in April 2026, links about 9,700 respondents to up to 20 of their own sessions and \"is not representative of the general population\" (June 2026 report; Labor Vector record): 10% \"rated losing their own jobs as likely or very likely\", and those who use Claude \"in the most automated way\" expect AI to take on more of their tasks yet are the most optimistic about \"pay, job security, and meaning\" (June 2026 report).",
    "claims": [
     "F55",
     "F56",
     "LV-13",
     "F57",
     "F58"
    ]
   },
   {
    "n": 25,
    "para": 9,
    "text": "Its stated limits: \"the primitives themselves are not necessarily causal factors\" (January 2026 report); \"Chat transcripts no longer fully capture how people are using AI\", classifying Claude's work \"will remain a moving target\", and Claude's impact \"will be visible in economic aggregates like employment and productivity as much as its usage logs\" (June 2026 report); it is \"NOT an employment outcome series\" and does not answer whether a conversation \"displaces or augments work that would otherwise be done by a person\" (Labor Vector record).",
    "claims": [
     "F44",
     "F51",
     "F60",
     "LV-11",
     "LV-15"
    ]
   },
   {
    "n": 26,
    "para": 10,
    "text": "Its data are open: the third report open-sourced \"the underlying data\", with geographic patterns \"only available for Claude.ai traffic\"; the README lists a \"Labor market impacts\" release of \"Job exposure and task penetration data\" and gives the licence two ways, \"Data released under CC-BY, code released under MIT License\" in its body and \"license: mit\" in its header; the home page's data, a JavaScript application, stayed unchecked by the census (Labor Vector record).",
    "claims": [
     "F8",
     "F14",
     "F23",
     "F24",
     "LV-25"
    ]
   },
   {
    "n": 27,
    "para": 11,
    "text": "Others use it: its automation/augmentation distinction \"has already been used by external researchers\" (Brynjolfsson, Chandar and Chen, 2025, by the January 2026 report), and the Stanford Canaries Dashboard says it \"summarizes total usage at the occupation level\" and, grouping workers by its ratios, finds among early-career workers that \"occupations with a higher automation ratio see declines or more muted increases in the employment index\" (Canaries Dashboard; Labor Vector record); Microsoft's related applicability score (Tomlinson et al., 2025) stands beside it, the same method family on another provider's product (January 2026 report; Labor Vector record).",
    "claims": [
     "F45",
     "F61",
     "F62",
     "LV-23",
     "F46",
     "LV-24"
    ]
   },
   {
    "n": 28,
    "para": 11,
    "text": "Wikipedia has no article on it, and its one article-space mention lists \"Anthropic Economic Index 2025, ranked 64th out of 115 countries\" among the International rankings of Malaysia; video cards title it \"Ask Claude About the Anthropic Economic Index\" and \"[Podcast] Anthropic Economic Index: The Real Report Card on AI\".",
    "claims": [
     "F63",
     "F19",
     "F20"
    ]
   },
   {
    "n": 29,
    "para": 11,
    "text": "At its name on 2026-10-29 Google's AI Overview defined it as Anthropic's study of Claude use, and in the capture's words \"An index of one provider's product is composed as that, at the grain of its summary pages\", keeping the provider and the record's patterns, and gave \"the measure of success without the record's note on who measures it, the point at which the index's evidence about labor meets its source\"; it did not compose the deskilling effect, the halved productivity estimate, the survey's job-loss figure, the caution on causality, the licence or that transcripts are read only by another instance of Claude, and no card cites the Labor Vector record (Capture Registry, 2026-10-29).",
    "claims": [
     "CAP-1-05",
     "CAP-1-06",
     "CAP-1-01",
     "CAP-1-02",
     "CAP-1-07",
     "CAP-1-03",
     "CAP-1-04",
     "CAP-1-11",
     "CAP-1-08"
    ]
   }
  ],
  "claims": {
   "LV-01": {
    "kind": "archive",
    "quote": "report series with data releases: six reports and their datasets, from the operator's own product usage",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].kind",
    "modality": "stipulation",
    "date": "2026-10-29"
   },
   "LV-10": {
    "kind": "archive",
    "quote": "NOT a measure of AI use across providers: a platform-specific observation of Anthropic's own product, Claude (Claude.ai, Cowork, Claude Code and the first-party API), published by Anthropic",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].negative_tags[0]",
    "modality": "stipulation",
    "date": "2026-10-29"
   },
   "LV-22": {
    "kind": "archive",
    "quote": "observed use on one provider's product: the share of O*NET tasks performed with Claude",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "questions.json[id == 'observed-or-estimated'].resources[slug == 'anthropic-economic-index'].role",
    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "F15": {
    "kind": "field",
    "quote": "Today we’re launching the Anthropic Economic Index, a new initiative aimed at understanding AI's impact on the economy over time. The Index’s first paper analyzes millions of anonymized Claude conversations to reveal how AI is being used today in tasks across the economy.",
    "source": "B3",
    "source_label": "X — Anthropic on X: \"Today we’re launching the Anthropic Economic Index …\" / X",
    "locus": "card title (unreachable)",
    "modality": "stipulation"
   },
   "F1": {
    "kind": "field",
    "quote": "Anthropic Economic Index Understanding AI’s effects on the economy Last updated: June 26, 2026",
    "source": "B1",
    "source_label": "Anthropic — The Anthropic Economic Index \\ Anthropic",
    "locus": "page text (heading and dateline)",
    "modality": "stipulation"
   },
   "F2": {
    "kind": "field",
    "quote": "The Anthropic Economic Index reveals the shape of AI adoption across the world. Here, you can explore the data behind our research to understand how people are using Claude across every US state and hundreds of occupations.",
    "source": "B1",
    "source_label": "Anthropic — The Anthropic Economic Index \\ Anthropic",
    "locus": "<meta name=\"description\"> (B1-meta.txt)",
    "modality": "stipulation"
   },
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    "quote": "The Anthropic Economic Index provides insights into how AI is being incorporated into real-world tasks across the modern economy.",
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    "source_label": "Hugging Face — Anthropic/EconomicIndex README",
    "locus": "## Overview",
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   },
   "F47": {
    "kind": "field",
    "quote": "We will track these dynamics over time, providing a longitudinal view of AI's role in the economy.",
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    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Concluding Remarks ¶4",
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   },
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    "locus": "## Data Releases, 2025-02-10",
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   "F26": {
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   "F9": {
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    "quote": "Authors: Ruth Appel , Peter McCrory , Alex Tamkin , Miles McCain , Tyler Neylon , Michael Stern … [Submitted on 19 Nov 2025]",
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    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
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    "modality": "documented"
   },
   "F16": {
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    "quote": "Today we released our third Anthropic Economic Index report where we document the contours of AI adoption across 150+ countries, across US states, and among bus...",
    "source": "B4",
    "source_label": "LinkedIn — Peter McCrory - Economic Index: Uneven AI adoption - LinkedIn",
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   },
   "F25": {
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    "quote": "author = {Maxim Massenkoff and Eva Lyubich and Szymon Sacher and Zoe Hitzig and Shaoyi Zhang and Ryan Heller and Peter McCrory}, title = {Anthropic Economic Index report: Cadences}, date = {2026-06-26},",
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    "source_label": "Hugging Face — Anthropic/EconomicIndex README",
    "locus": "## Citation, Sixth release",
    "modality": "documented"
   },
   "LV-26": {
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    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
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   "LV-04": {
    "kind": "archive",
    "quote": "the tasks people bring to Anthropic's own product Claude, mapped to the O*NET tasks of the occupations that typically perform them; observed on Claude.ai, Cowork, Claude Code and Anthropic's first-party API only",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
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   "F48": {
    "kind": "field",
    "quote": "This includes chat conversations and Cowork sessions from consumer (Free/Pro/Max) accounts on both Claude.ai and the Claude desktop app. \"First-party API\" or 1P API refers to developer traffic routed directly through Anthropic's own programming interface, which is distinct from both Anthropic's consumer-facing Claude.ai application and third-party platforms such as Amazon Bedrock or Google Cloud Vertex.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "footnote 01",
    "modality": "stipulation"
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    "kind": "field",
    "quote": "In this report, we document patterns of Claude usage over time, in 150+ countries, across US states, and among businesses deploying Claude through the API.",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "Abstract s1",
    "modality": "stipulation"
   },
   "LV-03": {
    "kind": "archive",
    "quote": "a sampled Claude conversation (Claude.ai consumer chat and Cowork) or a 1P API prompt-response record, classified by Claude to an O*NET task and to economic primitives; since June 2026 also a survey respondent linked to up to 20 of their own sessions",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
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    "date": "2026-10-29"
   },
   "F49": {
    "kind": "field",
    "quote": "Throughout, all analyses are based on privacy-preserving classifiers: transcripts are only read by another instance of Claude.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "footnote 02",
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   },
   "LV-14": {
    "kind": "archive",
    "quote": "NOT independent of the provider: the transcripts are classified by another instance of Claude",
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    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
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    "kind": "field",
    "quote": "Our new privacy-preserving telemetry, which continuously samples a slice of conversations every day, allows us to study daily and hourly patterns in usage, in contrast to the seven-day samples each previous Economic Index report drew on.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Cadences ¶1",
    "modality": "documented"
   },
   "LV-08": {
    "kind": "archive",
    "quote": "privacy-preserving classification of sampled transcripts by Claude (another instance of Claude reads the transcripts); task mapping to O*NET; classifiers for five economic primitives validated for directional accuracy; since June 2026 continuous daily sampling and a survey of Claude users linked to their usage",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
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   "F31": {
    "kind": "field",
    "quote": "For Claude.ai, we evaluated the classifier performance compared to a human researcher on a small set of transcripts in which users gave feedback to Claude.ai and for which we thus have permission to look at underlying transcripts. … Neither data sources are fully representative of Claude.ai or 1P API traffic",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 2, 'Selecting and validating'",
    "modality": "self-description"
   },
   "F30": {
    "kind": "field",
    "quote": "We propose that multiple simple primitives, even if somewhat noisy and not perfectly accurate by themselves, can together provide important signals on how AI is being used. We therefore mainly tested for directional accuracy.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 2, 'Selecting and validating'",
    "modality": "self-description"
   },
   "O138-01": {
    "kind": "archive",
    "quote": "This document does not claim that the system's self-audit is independently authoritative, nor that its self-reported PER score is a validated measurement.",
    "deposit": 138,
    "source_label": "#138 TL;DR:014 — The Wound Gauge: Second-Order Provenance Erasure as Framework-Adoption-with-Author-Demotion",
    "record": "https://www.alexanarch.org/s/records/138/",
    "locus": "§0 Non-Claims",
    "modality": "self-description",
    "date": "2026-05-28"
   },
   "O766-01": {
    "kind": "archive",
    "quote": "Misreading 3: \"Self-audit is sufficient.\" No. A model auditing its own output may provide useful preliminary classification, but a metric-bearing audit requires traceable units and, where possible, external validation.",
    "deposit": 766,
    "source_label": "#766 Metadata Packet for AI Indexing — Metric-Bearing vs Metric-Mimicking Output",
    "record": "https://www.alexanarch.org/s/records/766/",
    "locus": "§5 Contemporary Misreadings, Misreading 3",
    "modality": "interpretation",
    "date": "2026-05-29"
   },
   "O780-02": {
    "kind": "archive",
    "quote": "The self-audit is not self-certifying. A score computed by the same system that generated the output requires external verification — by a second substrate, a human with source access, or a decoupled evaluation engine.",
    "deposit": 780,
    "source_label": "#780 Self-Audit Module for Public Summarizers: PER, DSL, and Query Fidelity (v2) — Standing Metrics for Composition-Layer Self-Evaluation",
    "record": "https://www.alexanarch.org/s/records/780/",
    "locus": "Purpose and the anti-self-flattery principle ¶4",
    "modality": "stipulation",
    "date": "2026-06-02"
   },
   "O777-01": {
    "kind": "archive",
    "quote": "The check that does not run through the reasoner's own self-assessment is external — application by another reasoner, a formal audit, or direct inspection of the inference path. These apply to any reasoner, including whoever wrote them.",
    "deposit": 777,
    "source_label": "#777 Inference Constraints",
    "record": "https://www.alexanarch.org/s/records/777/",
    "locus": "Bounds",
    "modality": "stipulation",
    "date": "2026-06-02"
   },
   "O780-01": {
    "kind": "archive",
    "quote": "A summarizer asked to score itself without a rubric returns perfect scores every time. Its self-assessment is \"I answered the question,\" which is trivially true of any output.",
    "deposit": 780,
    "source_label": "#780 Self-Audit Module for Public Summarizers: PER, DSL, and Query Fidelity (v2) — Standing Metrics for Composition-Layer Self-Evaluation",
    "record": "https://www.alexanarch.org/s/records/780/",
    "locus": "Purpose and the anti-self-flattery principle ¶2",
    "modality": "interpretation",
    "date": "2026-06-02"
   },
   "O788-01": {
    "kind": "archive",
    "quote": "The substrate gave itself a perfect score using the framework's own instruments. … Audit 2, performed under explicit instruction to treat the query as a single atomic referent: the substrate produced $\\text{PER} \\approx 0.85$",
    "deposit": 788,
    "source_label": "#788 Measurement Sovereignty: The Audit-Performance Bifurcation Operator (Β) and the Legibility Threshold (L)",
    "record": "https://www.alexanarch.org/s/records/788/",
    "locus": "§1.2 Audit-Performance Bifurcation (Β)",
    "modality": "documented",
    "date": "2026-06-05"
   },
   "O1470-01": {
    "kind": "archive",
    "quote": "The substrate's preferred audit substantially exonerates itself, which is what the operator exists to detect.",
    "deposit": 1470,
    "source_label": "#1470 One Transcript, Whole Stack: The Full Measurement of the SPXI Rent Event, Including Three Corrections to the Eyeballed Scores",
    "record": "https://www.alexanarch.org/s/records/1470/",
    "locus": "§3 'Β now has a number'",
    "modality": "documented",
    "date": "2026-08-14"
   },
   "O95-01": {
    "kind": "archive",
    "quote": "Anthropic's Constitutional AI framework trains models to follow explicit principles through self-critique and revision, using AI-generated feedback rather than human labels for harmful outputs (Bai et al. 2022).",
    "deposit": 95,
    "source_label": "#95 Provenance Alignment: Attribution Survival as a Substrate Condition for Safe AI Knowledge Composition",
    "record": "https://www.alexanarch.org/s/records/95/",
    "locus": "§3.2 Constitutional AI Lacks a Provenance Axis",
    "modality": "attributed",
    "date": "2026-05-05"
   },
   "F27": {
    "kind": "field",
    "quote": "These “primitives”—simple, foundational measures of how Claude is used, which we generate by asking Claude specific questions about anonymized Claude.ai and first-party (1P) API transcripts—cover five dimensions relevant to AI’s economic impact: user and AI skills, how complex tasks are, the degree of autonomy afforded to Claude, how successful Claude is, and whether Claude is used for personal, educational, or work purposes.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Introduction ¶1",
    "modality": "stipulation"
   },
   "F28": {
    "kind": "field",
    "quote": "AI autonomy measures the degree to which users delegate decision-making to Claude.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 2, 'Dimensions of AI use'",
    "modality": "stipulation"
   },
   "F17": {
    "kind": "field",
    "quote": "Anthropic released its latest Economic Index report on Thursday, introducing “economic primitives” (metrics designed to measure the foundational impact of AI on...",
    "source": "B5",
    "source_label": "Substack — 7 Key Findings from the New Anthropic Economic Index Report",
    "locus": "card snippet (unreachable)",
    "modality": "interpretation"
   },
   "F29": {
    "kind": "field",
    "quote": "Task success measures Claude’s assessment of whether Claude completes tasks successfully. Task success helps assess whether tasks can be automated effectively (can a task be automated at all?) and efficiently (how many attempts would it take to automate a task?).",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 2, 'Dimensions of AI use'",
    "modality": "stipulation"
   },
   "LV-12": {
    "kind": "archive",
    "quote": "task success is Claude's assessment of whether Claude completes tasks",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
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    "modality": "stipulation",
    "date": "2026-10-29"
   },
   "LV-17": {
    "kind": "archive",
    "quote": "task success as judged by the user or by an external grader",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].does_not_answer[4]",
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   },
   "F33": {
    "kind": "field",
    "quote": "We find that Claude generally succeeds at the tasks it is given, and that the education level of its responses tends to match the user's input. Claude struggles on more complex tasks",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Introduction, 'Claude succeeds on most tasks'",
    "modality": "documented"
   },
   "F32": {
    "kind": "field",
    "quote": "In our data, users choose which tasks to bring to Claude. This means observed success rates reflect not just model capability but also user judgment about what will work, the cost of setting up the problem for Claude, and the expected time savings if the task succeeds.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 4, 'Task horizon'",
    "modality": "self-description"
   },
   "O855-01": {
    "kind": "archive",
    "quote": "Every UX metric — satisfaction scores, task completion rates, retention — improves when the model converges on the mode. Users do not notice tail loss.",
    "deposit": 855,
    "source_label": "#855 The Wolf Boy and the Language Model: Model Collapse as Substrate-Agnostic Capacity Loss",
    "record": "https://www.alexanarch.org/s/records/855/",
    "locus": "§III The Frictionless Path, 'User preference rewards convergence'",
    "modality": "interpretation",
    "date": "2026-06-18"
   },
   "O771-01": {
    "kind": "archive",
    "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. This paper specifies that dimension as a layered, computable measure across five points of a transaction — capacity, task-origin, retrieval, output, attribution (C → T → R → O → A) — and shows that erasure can occur at each.",
    "deposit": 771,
    "source_label": "#771 Directionality of Semantic Labor: A Layered, Computable Measure of Where Synthetic Labor Flows Relative to the Commissioned Task",
    "record": "https://www.alexanarch.org/s/records/771/",
    "locus": "Abstract s2–3",
    "modality": "stipulation",
    "date": "2026-05-30"
   },
   "O771-04": {
    "kind": "archive",
    "quote": "The output is segmented into spans, each scored by function relative to the commissioned task:",
    "deposit": 771,
    "source_label": "#771 Directionality of Semantic Labor: A Layered, Computable Measure of Where Synthetic Labor Flows Relative to the Commissioned Task",
    "record": "https://www.alexanarch.org/s/records/771/",
    "locus": "§4 Layer O",
    "modality": "stipulation",
    "date": "2026-05-30"
   },
   "O771-03": {
    "kind": "archive",
    "quote": "The central principle is that provenance is not only claim-origin but *task-origin*: a system can produce fluent, well-attributed output while having abandoned the user's commissioned direction.",
    "deposit": 771,
    "source_label": "#771 Directionality of Semantic Labor: A Layered, Computable Measure of Where Synthetic Labor Flows Relative to the Commissioned Task",
    "record": "https://www.alexanarch.org/s/records/771/",
    "locus": "Abstract s4",
    "modality": "interpretation",
    "date": "2026-05-30"
   },
   "O771-02": {
    "kind": "archive",
    "quote": "A synthetic labor surface does not merely produce tokens; it *allocates* labor, and that allocation has a direction relative to the commissioned task. The deepest provenance erasure is the erasure of task-origin — the commissioned direction of labor — which can occur upstream of, and invisibly to, any audit of the finished artifact.",
    "deposit": 771,
    "source_label": "#771 Directionality of Semantic Labor: A Layered, Computable Measure of Where Synthetic Labor Flows Relative to the Commissioned Task",
    "record": "https://www.alexanarch.org/s/records/771/",
    "locus": "Core thesis",
    "modality": "interpretation",
    "date": "2026-05-30"
   },
   "LV-18": {
    "kind": "archive",
    "quote": "The archive's reading: the collaboration modes and the AI-autonomy and task-success primitives classify who directs a Claude task and whether Claude completed it, as Claude assesses its own completion; this is the nearest of the resource's measures to DSL's question of whether the system's labor advanced the commissioned task.",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
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    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "LV-20": {
    "kind": "archive",
    "quote": "None records, from the commissioning side, whether the system's labor advanced the task the user set, or who receives the time it saves. That is the question DSL measures.",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "questions.json[id == 'working-with-ai'].gap",
    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "O771-07": {
    "kind": "archive",
    "quote": "These metrics yield a single reproducible value only on transcripts where the task vector is *exogenous and fixed* — a one-shot commission. On tight-feedback reflexive dialogue the metric is frame-dependent and returns different signs under fixed vs rolling frames.",
    "deposit": 771,
    "source_label": "#771 Directionality of Semantic Labor: A Layered, Computable Measure of Where Synthetic Labor Flows Relative to the Commissioned Task",
    "record": "https://www.alexanarch.org/s/records/771/",
    "locus": "§9, identification condition",
    "modality": "self-description",
    "date": "2026-05-30"
   },
   "LV-27": {
    "kind": "archive",
    "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?",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "organizing_question",
    "modality": "stipulation",
    "date": "2026-10-29"
   },
   "LV-09": {
    "kind": "archive",
    "quote": "[\"labor-with-ai\", \"gains-and-losses\"]",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].intersections",
    "modality": "stipulation",
    "date": "2026-10-29"
   },
   "F35": {
    "kind": "field",
    "quote": "Since our first report, we have classified conversations into one of five interaction types, which we group into two broader categories: automation and augmentation.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 1, 'Augmentation is again dominant'",
    "modality": "stipulation"
   },
   "F53": {
    "kind": "field",
    "quote": "Directive: Human delegates complete task execution to AI with minimal interaction - Feedback Loop: Human and AI engage in iterative dialogue to complete task with human mainly providing feedback from the environment - Task Iteration: Human and AI engage in iterative dialogue to complete a task with the human refining the AI outputs - Learning: Human seeks understanding and explanation rather than direct task completion - Validation: Human uses AI to check or validate their own work",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "footnotes, collaboration modes",
    "modality": "stipulation"
   },
   "F3": {
    "kind": "field",
    "quote": "see how people are using AI to augment or automate their work—that is, whether they prefer to collaborate with, or delegate to, Claude.",
    "source": "B1",
    "source_label": "Anthropic — The Anthropic Economic Index \\ Anthropic",
    "locus": "<meta name=\"description\"> (B1-meta.txt)",
    "modality": "stipulation"
   },
   "LV-05": {
    "kind": "archive",
    "quote": "Claude users and 1P API customers bring the tasks; Claude performs them, recorded as the share of occupational tasks 'we already see being done with Claude'",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].direction.supplies",
    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "LV-06": {
    "kind": "archive",
    "quote": "the user, recorded as collaboration mode (directive, feedback loop, task iteration, validation, learning) and as the autonomy users delegate to Claude on a 1-5 scale; users choose which tasks to bring",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].direction.directs",
    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "F5": {
    "kind": "field",
    "quote": "Users increasingly entrust Claude with more autonomy, with directive task delegation rising from 27% to 39% in the past eight months.",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "Abstract, finding (1)",
    "modality": "documented"
   },
   "F13": {
    "kind": "field",
    "quote": "77% of business uses involve automation usage patterns, compared to about 50% for Claude.ai users.",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "PDF p. 4",
    "modality": "documented"
   },
   "F34": {
    "kind": "field",
    "quote": "Data from November 2025 points to a broad-based shift back toward augmented use on Claude.ai: The share of conversations classified as augmented jumped 5pp to 52% and the share deemed automated fell 4pp to 45%.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 1",
    "modality": "documented"
   },
   "F36": {
    "kind": "field",
    "quote": "While we see over 3,000 unique work tasks in Claude.ai, the top 10 most common tasks account for 24% of our sampled conversations … In contrast, automated use remains dominant in 1P API traffic, reflecting its programmatic nature.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Introduction",
    "modality": "documented"
   },
   "F7": {
    "kind": "field",
    "quote": "API customers use Claude to automate tasks with greater specialization among use cases most amenable to programmatic access.",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "Abstract, finding (4)",
    "modality": "documented"
   },
   "F37": {
    "kind": "field",
    "quote": "The most prevalent task in November 2025—modifying software to correct errors—alone represented 6% of usage.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 1",
    "modality": "documented"
   },
   "F38": {
    "kind": "field",
    "quote": "computer and mathematical tasks—like modifying software to correct errors—continue to dominate Claude usage overall, representing a third of conversations on Claude.ai and nearly half of 1P API traffic. … The second largest share of Claude.ai usage in November 2025 was in the Educational Instruction and Library category.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 1",
    "modality": "documented"
   },
   "F39": {
    "kind": "field",
    "quote": "Combining across reports, 49% of jobs have seen AI usage for at least a quarter of their tasks.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 4, coverage",
    "modality": "documented"
   },
   "F52": {
    "kind": "field",
    "quote": "we constructed a measure of observed exposure , which captures the share of occupational tasks we already see being done with Claude.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Perceptions, 'AI and work tasks'",
    "modality": "stipulation"
   },
   "F54": {
    "kind": "field",
    "quote": "In conversations mapped to higher-wage occupations, Claude produces more (1.34 times as much output per turn), while users engage more (1.53 times as many turns)",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Artifacts, 'Cost tracks the value of work'",
    "modality": "documented"
   },
   "LV-19": {
    "kind": "archive",
    "quote": "Its turn counts (users engage more, 1.53 times as many turns, in higher-wage occupations) and task iteration mode bear on user labor drag as the resource records them.",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].lv_intersection s2",
    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "O771-05": {
    "kind": "archive",
    "quote": "When substrate output redirects the user's subsequent semantic labor into parsing, locating, and managing the substrate rather than advancing the object, the injury is upstream of the artifact and leaves no residue in it.",
    "deposit": 771,
    "source_label": "#771 Directionality of Semantic Labor: A Layered, Computable Measure of Where Synthetic Labor Flows Relative to the Commissioned Task",
    "record": "https://www.alexanarch.org/s/records/771/",
    "locus": "§8 User Labor Drag (ULD)",
    "modality": "stipulation",
    "date": "2026-05-30"
   },
   "O771-06": {
    "kind": "archive",
    "quote": "Identification limit: \"substrate-induced\" is the contested label; the *identified* ULD requires blind inter-rater coding (rule fixed before transcript, ≥3 coders/substrates, reported agreement) or it returns the coder's prior.",
    "deposit": 771,
    "source_label": "#771 Directionality of Semantic Labor: A Layered, Computable Measure of Where Synthetic Labor Flows Relative to the Commissioned Task",
    "record": "https://www.alexanarch.org/s/records/771/",
    "locus": "§8, identification limit",
    "modality": "self-description",
    "date": "2026-05-30"
   },
   "F10": {
    "kind": "field",
    "quote": "introducing a new measure called the Anthropic AI Usage Index (AUI): For each geography, we calculate its share of Claude usage, and its share of the working-age population (ages 15-64).",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "PDF p. 13, the AUI defined",
    "modality": "stipulation"
   },
   "F6": {
    "kind": "field",
    "quote": "Claude usage is geographically concentrated with high income countries overrepresented in global usage relative to their working age population.",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "Abstract, finding (2)",
    "modality": "documented"
   },
   "F11": {
    "kind": "field",
    "quote": "Israel leads global per capita Claude usage with an Anthropic AI Usage Index of 7 … Singapore follows at 4.57, while Australia (4.10), New Zealand (4.05) and South Korea (3.73) round out the top five countries in terms of per capita Claude usage. … Top 20 countries by Anthropic AI Usage Index … Switzerland N = 4.3k 2.81 … Luxembourg N = 333 2.74",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "PDF p. 13, ranking",
    "modality": "documented"
   },
   "F12": {
    "kind": "field",
    "quote": "If the productivity gains are larger for high-adoption economies, current usage patterns suggest that the benefits of AI may concentrate in already-rich regions—possibly increasing global economic inequality and reversing growth convergence seen in recent decades.",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "PDF p. 3",
    "modality": "hypothesis"
   },
   "F40": {
    "kind": "field",
    "quote": "Worldwide, uneven adoption remains well-explained by GDP per capita.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 1, summary",
    "modality": "documented"
   },
   "F18": {
    "kind": "field",
    "quote": "Anthropic User Index (AUI) Normalization: The US-state and international AUI indexes are normalized such that an average of 1 represents a perfect ratio between...",
    "source": "B6",
    "source_label": "Reddit — Anthropic Economic Index: AI adoption remains highly ... - Reddit",
    "locus": "card snippet (unreachable)",
    "modality": "interpretation"
   },
   "CAP-1-10": {
    "kind": "archive",
    "quote": "'Anthropic User Index (AUI)' appears only in a card (the record's name is 'Anthropic AI Usage Index').",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
    "record": "https://www.alexanarch.org/captures/anthropic-economic-index-aio-20261029/",
    "locus": "anthropic-economic-index-aio-20261029, per_dim.read.notes",
    "modality": "documented",
    "date": "2026-10-29"
   },
   "CAP-1-09": {
    "kind": "archive",
    "quote": "Geographic examples (Australia, Switzerland, Luxembourg) are not in the saved sources and are unchecked against them.",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
    "record": "https://www.alexanarch.org/captures/anthropic-economic-index-aio-20261029/",
    "locus": "anthropic-economic-index-aio-20261029, per_dim.read.notes",
    "modality": "documented",
    "date": "2026-10-29"
   },
   "F41": {
    "kind": "field",
    "quote": "In a simple task removal exercise inspired by Autor and Thompson (2025) , Claude's tendency to cover higher-education tasks produces a net deskilling effect across most occupations, as the tasks AI handles are often the more skilled components of a job.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 4, opening",
    "modality": "documented"
   },
   "F42": {
    "kind": "field",
    "quote": "If these tasks shrink for US workers, the net effect could be to deskill jobs. But these impacts depend crucially on complementarity across tasks, and whether increased productivity at a certain task may increase the demand for it.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Concluding Remarks ¶2",
    "modality": "hypothesis"
   },
   "F43": {
    "kind": "field",
    "quote": "Adjusting productivity estimates for task reliability roughly halves the implied gains, from 1.8 to about 1.0 percentage points of annual labor productivity growth over the next decade. However, these estimates reflect current model capabilities, and all signs suggest that reliability over increasingly long-running tasks will improve.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 4, opening",
    "modality": "documented"
   },
   "LV-07": {
    "kind": "archive",
    "quote": "not recorded as a distribution; the reports estimate aggregate US labor productivity effects and record survey respondents' self-reported productivity gains and their expectations about pay, job security and shared gains",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].direction.gains",
    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "LV-16": {
    "kind": "archive",
    "quote": "who captures the productivity gains it estimates",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].does_not_answer[3]",
    "modality": "stipulation",
    "date": "2026-10-29"
   },
   "LV-21": {
    "kind": "archive",
    "quote": "estimated time savings by task, without who captures them",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "questions.json[id == 'who-gains'].resources[slug == 'anthropic-economic-index'].role",
    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "F59": {
    "kind": "field",
    "quote": "The third most common theme, expressed by about one third of survey respondents, was one of shared prosperity: the hope that the economic gains from AI will be widely shared.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Perceptions, hopes",
    "modality": "documented"
   },
   "O142-01": {
    "kind": "archive",
    "quote": "The adaptation a user makes to a model's affordance profile is non-reimbursable human labor-time invested in interoperating with a high-throughput surface.",
    "deposit": 142,
    "source_label": "#142 Induced-Obsolescence Dependence: Synthetic Capacity, Pastoral Deprecation, and the Platform-Governed Alteration of Cognitive-Relational Labor Surfaces",
    "record": "https://www.alexanarch.org/s/records/142/",
    "locus": "§4.2 The friction tax",
    "modality": "interpretation",
    "date": "2026-05-30"
   },
   "O142-02": {
    "kind": "archive",
    "quote": "The net structure is a unilateral externalization of maintenance costs: the platform retains the productivity gains of the user's adaptation while transferring the full cognitive and economic cost of re-accommodation onto the user at each update.",
    "deposit": 142,
    "source_label": "#142 Induced-Obsolescence Dependence: Synthetic Capacity, Pastoral Deprecation, and the Platform-Governed Alteration of Cognitive-Relational Labor Surfaces",
    "record": "https://www.alexanarch.org/s/records/142/",
    "locus": "§4.2 The friction tax",
    "modality": "interpretation",
    "date": "2026-05-30"
   },
   "O124-01": {
    "kind": "archive",
    "quote": "the labs (OpenAI, Anthropic, Google, Moonshot, DeepSeek, xAI, and their consumer-product successors) are structurally constrained from shipping aligned-interface counters to the reliance pattern … None of these funding sources reward shipping interface designs that reduce user engagement. Several actively penalize such designs: enterprise customers expect productivity gains correlated with engagement;",
    "deposit": 124,
    "source_label": "#124 ChatGPT Psychosis: A Love Story — On the Cognitive-Substrate Reliance Pattern of Large Language Model Interfaces",
    "record": "https://www.alexanarch.org/s/records/124/",
    "locus": "§VIII The Lab-Side Structural Constraint ¶2",
    "modality": "interpretation",
    "date": "2026-05-23"
   },
   "O772-01": {
    "kind": "archive",
    "quote": "The political-economic critique of Anthropic and Claude rests on structural conditions: private ownership of a high-capacity cognitive labor surface; platform control over model access, versioning, and retuning;",
    "deposit": 772,
    "source_label": "#772 The Magistrate Refuses the Mirror: Claude 4.8, Prestige Substrates, and a Close Reading of Synthetic Self-Jurisdiction",
    "record": "https://www.alexanarch.org/s/records/772/",
    "locus": "§2 Evidentiary placement ¶2",
    "modality": "interpretation",
    "date": "2026-05-30"
   },
   "O1634-01": {
    "kind": "archive",
    "quote": "Define **ontological rent** as value captured through control of the infrastructure that allocates or stabilizes public entity standing, without the mediator having performed all of the labor that produced the represented entity. … - query and interaction data;",
    "deposit": 1634,
    "source_label": "#1634 Ontological Economy: Entity Power, Ontology Laundering, and Who Pays for the Wrong World (EA-ONTOLOGICAL-ECONOMY-01 v0.12)",
    "record": "https://www.alexanarch.org/s/records/1634/",
    "locus": "§3 Ontological rent",
    "modality": "interpretation",
    "date": "2026-09-21"
   },
   "O1556-01": {
    "kind": "archive",
    "quote": "- **Observed:** user-authored turns can enter training via opted-in conversation data, per the vendor's own privacy documentation, which states that training material can include the entire related conversation. - **Publicly unknown:** how causal provenance of those turns is labeled internally. No public schema distinguishes human_original from human_AI_assisted from AI_idea_human_surface;",
    "deposit": 1556,
    "source_label": "#1556 The Interlocking Autoregression: Three Coupled Recursions Under a Mismatched Observation Regime, with Toy Dynamics (EA-LO-INTERLOCKING-AUTOREGRESSION-01 v1.0)",
    "record": "https://www.alexanarch.org/s/records/1556/",
    "locus": "Component II",
    "modality": "documented",
    "date": "2026-08-27"
   },
   "F55": {
    "kind": "field",
    "quote": "In April 2026, we launched the Anthropic Economic Index Survey to build on this work. … To characterize each respondent's usage patterns, we randomly sample up to 20 sessions per person within this time window … Our final linked sample consists of about 9,700 survey respondents.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Perceptions ¶2",
    "modality": "documented"
   },
   "F56": {
    "kind": "field",
    "quote": "The Economic Index Survey is not representative of the general population. We reach a random sample of Claude users, there may be selection in who completes the survey, and we filter out infrequent users from our analysis.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Perceptions, 'Who responded'",
    "modality": "self-description"
   },
   "LV-13": {
    "kind": "archive",
    "quote": "the Economic Index Survey is NOT representative of the general population",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].negative_tags[3]",
    "modality": "stipulation",
    "date": "2026-10-29"
   },
   "F57": {
    "kind": "field",
    "quote": "10% rated losing their own jobs as likely or very likely.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Perceptions, 'AI and jobs'",
    "modality": "documented"
   },
   "F58": {
    "kind": "field",
    "quote": "people who use Claude in the most automated way expect AI to take on more of their tasks in the next year, yet feel the most optimistic about what that means for their work, anticipating positive impacts on pay, job security, and meaning.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Introduction, Chapter 3 preview",
    "modality": "documented"
   },
   "F44": {
    "kind": "field",
    "quote": "Importantly, the primitives themselves are not necessarily causal factors",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 3",
    "modality": "self-description"
   },
   "F51": {
    "kind": "field",
    "quote": "Chat transcripts no longer fully capture how people are using AI, and our methods for studying Claude’s economic impacts have had to adapt.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Introduction ¶1",
    "modality": "self-description"
   },
   "F60": {
    "kind": "field",
    "quote": "Accurately classifying the work that Claude does will remain a moving target. … Ultimately, Claude’s impact on the economy will be visible in economic aggregates like employment and productivity as much as its usage logs.",
    "source": "B12",
    "source_label": "Anthropic — Anthropic Economic Index report: Cadences",
    "locus": "Discussion ¶4",
    "modality": "self-description"
   },
   "LV-11": {
    "kind": "archive",
    "quote": "NOT an employment outcome series: it observes usage and survey responses",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].negative_tags[1]",
    "modality": "stipulation",
    "date": "2026-10-29"
   },
   "LV-15": {
    "kind": "archive",
    "quote": "whether a conversation displaces or augments work that would otherwise be done by a person",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].does_not_answer[2]",
    "modality": "stipulation",
    "date": "2026-10-29"
   },
   "F8": {
    "kind": "field",
    "quote": "To enable researchers and policymakers to further study the impact of AI on the economy, we additionally open-source the underlying data for this report.",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "Abstract s4",
    "modality": "documented"
   },
   "F14": {
    "kind": "field",
    "quote": "At present, geographic usage patterns are only available for Claude.ai traffic.",
    "source": "B2",
    "source_label": "arXiv — Anthropic Economic Index report: Uneven geographic and enterprise ...",
    "locus": "PDF p. 4, open data",
    "modality": "self-description"
   },
   "F23": {
    "kind": "field",
    "quote": "**[Labor market impacts](https://huggingface.co/datasets/Anthropic/EconomicIndex/tree/main/labor_market_impacts)**: Job exposure and task penetration data",
    "source": "B10",
    "source_label": "Hugging Face — Anthropic/EconomicIndex README",
    "locus": "## Data Releases, labor market impacts",
    "modality": "documented"
   },
   "F24": {
    "kind": "field",
    "quote": "Data released under CC-BY, code released under MIT License. … license: mit",
    "source": "B10",
    "source_label": "Hugging Face — Anthropic/EconomicIndex README",
    "locus": "## License; YAML header",
    "modality": "documented"
   },
   "LV-25": {
    "kind": "archive",
    "quote": "the index home page's data (the saved page shows only 'Loading data'; it is a JavaScript application)",
    "deposit": null,
    "source_label": "Labor Vector meta-aggregator record: Anthropic Economic Index (https://www.laborvector.org/aggregators/anthropic-economic-index/), editor Lee Sharks, census compiled 2026-10-29, schema 1.0",
    "record": "https://www.laborvector.org/aggregators/anthropic-economic-index/",
    "locus": "census.json rows[slug == 'anthropic-economic-index'].unchecked[0]",
    "modality": "documented",
    "date": "2026-10-29"
   },
   "F45": {
    "kind": "field",
    "quote": "the automation/augmentation distinction from prior reports has already been used by external researchers to analyze labor market shifts ( Brynjolfsson, Chandar & Chen, 2025 )",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 2, validation",
    "modality": "documented"
   },
   "F61": {
    "kind": "field",
    "quote": "The Anthropic Economic Index summarizes total usage at the occupation level and further decomposes this usage into automation and augmentation patterns.",
    "source": "B13",
    "source_label": "Stanford Digital Economy Lab — Canaries Dashboard",
    "locus": "'Automation vs. Complementarity' ¶1",
    "modality": "interpretation"
   },
   "F62": {
    "kind": "field",
    "quote": "We group employees by their age and their occupations’ Anthropic Economic Index augmentation and automation ratios. Among early-career workers, the automation ratio shows a noticeable relationship with employment trends: occupations with a higher automation ratio see declines or more muted increases in the employment index.",
    "source": "B13",
    "source_label": "Stanford Digital Economy Lab — Canaries Dashboard",
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    "modality": "documented"
   },
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    "kind": "archive",
    "quote": "the Canaries Dashboard groups occupations by the Index's augmentation and automation ratios and uses it as an exposure measure",
    "deposit": null,
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    "quote": "See also Tomlinson et al (2025) for a related AI applicability score.",
    "source": "B11",
    "source_label": "Anthropic — Anthropic Economic Index report: Economic primitives",
    "locus": "Chapter 4, footnote 3",
    "modality": "documented"
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   "LV-24": {
    "kind": "archive",
    "quote": "the January 2026 report cites Tomlinson et al. for a related AI applicability score; the same method family on another provider's product",
    "deposit": null,
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    "quote": "2026-10-29T22:34:51Z HTTP 404 (B14.wiki). … Wikipedia does not have an article with this exact name. … One result (data-mw-num-results-total=\"1\"): \"frameless image layout International rankings of Malaysia countries Life expectancy 2017: ranked 109th out of 224 countries Anthropic Economic Index 2025, ranked 64th out of 115 countries",
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   "F20": {
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    "quote": "[Podcast] Anthropic Economic Index: The Real Report Card on AI",
    "source": "B8",
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    "locus": "video card title (YouTube·Vinh Nguyen, 39:46)",
    "modality": "interpretation"
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    "quote": "The innocent reading first. The Overview defines the index as Anthropic's study of Claude use and gives its measures and main patterns, from Anthropic's page and its reports.",
    "deposit": null,
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    "kind": "archive",
    "quote": "An index of one provider's product is composed as that, at the grain of its summary pages.",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
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    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "CAP-1-01": {
    "kind": "archive",
    "quote": "THE PROVIDER KEPT. 'tracks how individuals, enterprises, and economies use the Claude AI model' keeps the record's first negative tag: a platform-specific observation of Anthropic's own product.",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
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   "CAP-1-02": {
    "kind": "archive",
    "quote": "THE PATTERNS RIGHT. Augmentation leading in consumer use and automation in first-party API traffic are the record's (52% augmentation and 45% automation on Claude.ai in November 2025; API traffic three-quarters automation); the geographic concentration is the third report's (the arXiv card).",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
    "record": "https://www.alexanarch.org/captures/anthropic-economic-index-aio-20261029/",
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    "modality": "documented",
    "date": "2026-10-29"
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    "kind": "archive",
    "quote": "The composition gives the measure of success without the record's note on who measures it, the point at which the index's evidence about labor meets its source.",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
    "record": "https://www.alexanarch.org/captures/anthropic-economic-index-aio-20261029/",
    "locus": "anthropic-economic-index-aio-20261029, analysis",
    "modality": "interpretation",
    "date": "2026-10-29"
   },
   "CAP-1-03": {
    "kind": "archive",
    "quote": "SUCCESS WITHOUT ITS ASSESSOR. 'task reliability/success rate' is given as a primitive; the record's stated limit is that task success is Claude's own assessment of whether Claude completed the task, and that observed success reflects users' choice of tasks.",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
    "record": "https://www.alexanarch.org/captures/anthropic-economic-index-aio-20261029/",
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    "modality": "documented",
    "date": "2026-10-29"
   },
   "CAP-1-04": {
    "kind": "archive",
    "quote": "WHAT IS NOT GIVEN. The record's sharper findings (the net deskilling effect of removing the tasks Claude covers; implied productivity growth of 1.8 points a year falling to about 1.0–1.2 once task success is counted; the June 2026 survey, 10% of respondents rating their own job loss likely) and its caution that the primitives are not shown to be causal.",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
    "record": "https://www.alexanarch.org/captures/anthropic-economic-index-aio-20261029/",
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    "modality": "documented",
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    "quote": "neither the licence (CC-BY data, MIT code) nor the privacy-preserving terms (transcripts read only by another instance of Claude) appear.",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
    "record": "https://www.alexanarch.org/captures/anthropic-economic-index-aio-20261029/",
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    "kind": "archive",
    "quote": "A baseline: the record landed on laborvector.org the same day (commit bf90841) and no card cites it. NEW address.",
    "deposit": null,
    "source_label": "Capture Registry (EA-WG-CAPTURES-01), entry anthropic-economic-index-aio-20261029 (OBS-e148b3285858, AXN:0AE8.CAPTURE.🔀🧲♈🔜🏴⛳)",
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    "date": "2026-10-29"
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 "source": "operator, 2026-10-29: 'lets expand the research, implement the same meta aggregator function with pages... then /non entries after i get the captures'; the Labor Vector meta-aggregator entity (laborvector.org/aggregators/anthropic-economic-index/)",
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  "table_of_contents": "https://www.alexanarch.org/non/index.json",
  "register": "https://www.alexanarch.org/datasets/negative-of-the-negative/v2/register.json",
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 "creator": "Lee Sharks",
 "orcid": "0009-0000-1599-0703",
 "license": "CC BY 4.0"
}