{
 "row": "aiaaic-repository",
 "address": "aiaaic repository",
 "entity": "The AIAAIC Repository (aiaaic.org/aiaaic-repository), the collection of AI, algorithmic and automation incidents and controversies kept by AIAAIC ('AI, Algorithmic and Automation Incidents and Controversies'), started in June 2019 'as a private, professional project' (OECD catalogue), its content under CC BY-SA 4.0, its weekly newsletter AIAAIC Alert (aiaaicalert.substack.com, by Charlie Pownall); formalized in the MMRS meta-aggregator record of 2026-10-28",
 "procedure": "EA-NEGONT-02 v0.7 §3.4 (D/R/O), working; not frozen",
 "config": {
  "row": "aiaaic-repository",
  "address": "aiaaic repository",
  "addresses": [
   "aiaaic repository"
  ],
  "entity": "The AIAAIC Repository (aiaaic.org/aiaaic-repository), the collection of AI, algorithmic and automation incidents and controversies kept by AIAAIC ('AI, Algorithmic and Automation Incidents and Controversies'), started in June 2019 'as a private, professional project' (OECD catalogue), its content under CC BY-SA 4.0, its weekly newsletter AIAAIC Alert (aiaaicalert.substack.com, by Charlie Pownall); formalized in the MMRS meta-aggregator record of 2026-10-28",
  "row_type": "C (a public entity on which the archive bears: a database, one of the MMRS meta-aggregator's entities)",
  "aliases": [
   {
    "pattern": "\\bAIAAIC\\b",
    "flags": "i"
   },
   {
    "pattern": "\\baiaaic\\.org\\b",
    "flags": "i"
   },
   {
    "pattern": "\\bAI,? Algorithmic,? and Automation Incidents and Controversies\\b",
    "flags": "i"
   },
   {
    "pattern": "\\bAIAAIC Alert\\b",
    "flags": "i"
   },
   {
    "pattern": "\\bCharlie Pownall\\b",
    "flags": "i"
   }
  ],
  "classes": [
   {
    "term": "AI incident databases and incident tracking",
    "pattern": "\\b(AI )?incident (databases?|repositor(y|ies)|trackers?|tracking|monitors?|registr(y|ies))\\b",
    "flags": "i",
    "basis": "field: B2 (OECD catalogue entry, Tags): 'incident database'; B3 (EthicAI, 24 April 2025, 'The impetus for tracking AI incidents'): 'Enter the AI incident trackers.', and its title 'Tracking AI incidents: OECD AIM and AIAAIC Repository'"
   }
  ],
  "classes_note": "One class, sourced from the field by locus: the AIAAIC Repository as an incident database (B2, the OECD's tag) and as an AI incident tracker (B3, EthicAI). No field source places it in a class of the archive's own; the MMRS record's class (aggregators of machine-mediated reception work, the harm basin) is an archive source, ledgered as MMRS claims and not run as an O-class, since the brief confines classes to what B sources. Aliases: the name's acronym (case-insensitive; every hit is read, since the acronym has no other known referent), its domain, its expansion, its newsletter's name, and the newsletter writer the MMRS record names. Admission by reading (§3.4): a candidate is admitted when its sentence or paragraph makes a claim bearing on the AIAAIC Repository, or applies an archive category to incident databases as a class; a bare mention, a link list or a generic use of 'incident tracking' about another object is not a claim.",
  "exclude_deposits": [],
  "notes": "entity-keyed pass, 2026-10-29, on the brief rebuild/negative-of-the-negative/v09/BRIEF-NEW-ROW-AGGREGATOR.md; address 'aiaaic repository' (aiaaic-repository-aio-20261029, OBS-524198c4efed, ADDR-7feca6ebbaff), Google AI Overview (expanded), signed out, incognito. The archive's own records of the entity (the Capture Registry's findings and analysis, the MMRS meta-aggregator record) are ledgered beside the deposits as CAP-1-NN and MMRS-NN. Second pass: one citation hop forward and back from the deposit admitted by reading (#543).",
  "hop_from": [
   543
  ]
 },
 "texts_scanned": 1711,
 "counts": {
  "D_sentences": 1,
  "D_deposits": 1,
  "R_sentences": 1,
  "R_deposits": 1,
  "O_direct": 1,
  "O_class": 0,
  "O_deposits": 1,
  "H_candidates": 41
 },
 "per_deposit": {
  "D": {
   "543": 1
  },
  "R": {
   "543": 1
  },
  "O": {
   "543": 1
  }
 },
 "registry_entity_triples": [],
 "integrity_S5": [],
 "sha256": {
  "candidates-D.jsonl": "905bb8589af289bc66b8a50d154c125c8ca094f31e2ea27cacf9dce3b8913338",
  "candidates-R.jsonl": "0398427eed49333c3cbaeebe9204162790bd3eefaeff0d47514125e95b569bd4",
  "candidates-O.jsonl": "d5c7b9db22f1d82cdc7b2fb98f80a7497724b65f8106d38064c84c1570770a1d",
  "candidates-H.jsonl": "c356582b5c92cfa4bc9f07ca5d2bee09039dea53bbf2e54b7ce1c8bc21981faf"
 },
 "category_vocabulary": {
  "defines_concepts_and_lexical_mints": 11067
 },
 "note": "Candidates by string only. Admission by reading, recorded in the row's reading file; nothing here is admitted."
}