{ "slug": "provenance-erasure-1", "date": "2026-06-13", "surface": "Google AI Overview", "auth": "signed in", "ev": "ocr", "cites": 4, "per": null, "per_v": null, "mt": "CAPTURE", "d": "provenanceerasure.org ranks first. Defines provenance erasure as 'the systematic removal, loss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact.' 9+ sources cited including Institute of Historic Research. Zenodo shows Provenance After AI with the PER formula. Author name absent from Overview text.\n\nFull AI Mode transcript (17 June 2026):\nThe Provenance Erasure Rate (PER) is an evaluation metric used to measure attribution loss in artificial intelligence and synthetic composition systems.\nIt calculates the fraction of human-authored or source facts that a system's retrieval or generation process dissolves, omits, or fails to properly attribute when composing an answer.\nCore Metric: PER quantifies the magnitude of provenance loss within AI generation, summarization, or synthesis tools.\nProvisional Formula: PER = 1 - (retained provenance units / total attributable source claims)\nErasure Skew (Ω): A related measurement that evaluates whether attribution loss falls evenly across all sources, or systematically strips out low-power/small creators while favoring high-power sources.", "reading": null, "analysis": "provenanceerasure.org ranks first. Defines provenance erasure as 'the systematic removal, loss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact.' 9+ sources cited including Institute of Historic Research. Zenodo shows Provenance After AI with the PER formula. Author name absent from Overview text.\n\nFull AI Mode transcript (17 June 2026):\nThe Provenance Erasure Rate (PER) is an evaluation metric used to measure attribution loss in artificial intelligence and synthetic composition systems.\nIt calculates the fraction of human-authored or source facts that a system's retrieval or generation process dissolves, omits, or fails to properly attribute when composing an answer.\nCore Metric: PER quantifies the magnitude of provenance loss within AI generation, summarization, or synthesis tools.\nProvisional Formula: PER = 1 - (retained provenance units / total attributable source claims)\nErasure Skew (Ω): A related measurement that evaluates whether attribution loss falls evenly across all sources, or systematically strips out low-power/small creators while favoring high-power sources.", "transcript": "Q. provenance erasure x AlMode_- All Shopping Images Videos News + Al Overview EPO:\n\nProvenance erasure Is the systematic removal,\n\nloss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact. The concept spans multiple domains, from artificial intelligence to cultural history, and has profound implications for attribution, ownership, and truth. € Institute of Historic... +4\n\n© provenanceerasure.org . https://provenanceerasure.org\n\nProvenance Erasure — Lee Sharks\n\nProvenance erasure is the systematic removal or loss of a\n\nsource's authorial lineage, context, or ownership — particularly through Al synthesis, compression, or ...\n\n7) Zenodo : ~~ https://zenodo.org ;\n\nProvenance After Al\n\nQ. provenance erasure x AlMode_- All Shopping Images Videos News > Al Overview ees) Jo 17:\n\nProvenance erasure Is the systematic removal,\n\nloss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact. The concept spans multiple domains, from artificial intelligence to cultural history, and has profound implications for attribution, ownership, and truth. € Institute of Historic... +4\n\n© provenanceerasure.org .\n\nhttps://provenanceerasure.org ;\n\nProvenance Erasure — Lee Sharks\n\nProvenance erasure is the systematic removal or loss of a\n\nsource's authorial lineage, context, or ownership — particularly through Al synthesis, compression, or ...\n\nPp Zenodo .\n\n» — https://zenodo.org ;\n\nProvenance After Al\n\nFramework metric: Provenance Erasure Rate (PER), provisional, awaiting empirical validation. Provisional formula: PER = 1 - (retained provenance units / ...\n\no. Zenodo ‘ \"— httos://zenodo.orad °", "transcript_class": "OCR-READ, CHROME INTERLEAVED — NOT A PASTE. Answer text and browser furniture are mixed in one stream and have not been separated. Supports PRESENCE of wording, not RETENTION.", "transcript_complete": "TRUNCATED BY INTERFACE — a \"Show more\" control is in frame.", "transcript_read": "SEATED FROM OCR WITHOUT LINE-BY-LINE READING, 2026-08-13", "cite_list": null, "collisions": null, "oq": null, "imgs": [ "data/captures/provenance-erasure-rate-adoption/provenance-erasure-1.png", "data/captures/provenance-erasure-rate-adoption/provenance-erasure-2.png", "data/captures/provenance-erasure-rate-adoption/provenance-erasure-2.png", "data/captures/provenance-erasure-rate-adoption/provenance-erasure-1.png", "data/captures/provenance-erasure-recapture-20260811/screengrab-20260811-104919.png" ], "defects": [ "analysis-without-finding", "citations-null", "truncated-by-interface" ], "rounds": null, "rerun": "https://www.google.com/search?q=provenance+erasure", "q": "provenance erasure", "s": "Provenance & Erasure", "addr_id": "ADDR-b713bd9035da", "obs_id": "OBS-ecad39e5d924", "q_kind": null, "series": "3", "observations": [ { "slug": "provenance-erasure-1", "date": "2026-06-13", "surface": "Google AI Overview", "auth": "signed in", "ev": "ocr", "cites": null, "per": null, "per_v": null, "mt": "CAPTURE", "d": "provenanceerasure.org ranks first. Defines provenance erasure as 'the systematic removal, loss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact.' 9+ sources cited including Institute of Historic Research. Zenodo shows Provenance After AI with the PER formula. Author name absent from Overview text.\n\nFull AI Mode transcript (17 June 2026):\nThe Provenance Erasure Rate (PER) is an evaluation metric used to measure attribution loss in artificial intelligence and synthetic composition systems.\nIt calculates the fraction of human-authored or source facts that a system's retrieval or generation process dissolves, omits, or fails to properly attribute when composing an answer.\nCore Metric: PER quantifies the magnitude of provenance loss within AI generation, summarization, or synthesis tools.\nProvisional Formula: PER = 1 - (retained provenance units / total attributable source claims)\nErasure Skew (Ω): A related measurement that evaluates whether attribution loss falls evenly across all sources, or systematically strips out low-power/small creators while favoring high-power sources.", "reading": null, "analysis": "provenanceerasure.org ranks first. Defines provenance erasure as 'the systematic removal, loss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact.' 9+ sources cited including Institute of Historic Research. Zenodo shows Provenance After AI with the PER formula. Author name absent from Overview text.\n\nFull AI Mode transcript (17 June 2026):\nThe Provenance Erasure Rate (PER) is an evaluation metric used to measure attribution loss in artificial intelligence and synthetic composition systems.\nIt calculates the fraction of human-authored or source facts that a system's retrieval or generation process dissolves, omits, or fails to properly attribute when composing an answer.\nCore Metric: PER quantifies the magnitude of provenance loss within AI generation, summarization, or synthesis tools.\nProvisional Formula: PER = 1 - (retained provenance units / total attributable source claims)\nErasure Skew (Ω): A related measurement that evaluates whether attribution loss falls evenly across all sources, or systematically strips out low-power/small creators while favoring high-power sources.", "transcript": "Q. provenance erasure x AlMode_- All Shopping Images Videos News + Al Overview EPO:\n\nProvenance erasure Is the systematic removal,\n\nloss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact. The concept spans multiple domains, from artificial intelligence to cultural history, and has profound implications for attribution, ownership, and truth. € Institute of Historic... +4\n\n© provenanceerasure.org . https://provenanceerasure.org\n\nProvenance Erasure — Lee Sharks\n\nProvenance erasure is the systematic removal or loss of a\n\nsource's authorial lineage, context, or ownership — particularly through Al synthesis, compression, or ...\n\n7) Zenodo : ~~ https://zenodo.org ;\n\nProvenance After Al\n\nQ. provenance erasure x AlMode_- All Shopping Images Videos News > Al Overview ees) Jo 17:\n\nProvenance erasure Is the systematic removal,\n\nloss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact. The concept spans multiple domains, from artificial intelligence to cultural history, and has profound implications for attribution, ownership, and truth. € Institute of Historic... +4\n\n© provenanceerasure.org .\n\nhttps://provenanceerasure.org ;\n\nProvenance Erasure — Lee Sharks\n\nProvenance erasure is the systematic removal or loss of a\n\nsource's authorial lineage, context, or ownership — particularly through Al synthesis, compression, or ...\n\nPp Zenodo .\n\n» — https://zenodo.org ;\n\nProvenance After Al\n\nFramework metric: Provenance Erasure Rate (PER), provisional, awaiting empirical validation. Provisional formula: PER = 1 - (retained provenance units / ...\n\no. Zenodo ‘ \"— httos://zenodo.orad °", "transcript_class": "OCR-READ, CHROME INTERLEAVED — NOT A PASTE. Answer text and browser furniture are mixed in one stream and have not been separated. Supports PRESENCE of wording, not RETENTION.", "transcript_complete": "TRUNCATED BY INTERFACE — a \"Show more\" control is in frame.", "transcript_read": "SEATED FROM OCR WITHOUT LINE-BY-LINE READING, 2026-08-13", "cite_list": null, "collisions": null, "oq": null, "imgs": [ "data/captures/provenance-erasure-rate-adoption/provenance-erasure-1.png", "data/captures/provenance-erasure-rate-adoption/provenance-erasure-2.png" ], "defects": [ "truncated-by-interface", "citations-null", "analysis-without-finding" ], "rounds": null, "rerun": "https://www.google.com/search?q=provenance+erasure", "q": "provenance erasure", "s": "Frameworks", "addr_id": "ADDR-b713bd9035da", "obs_id": "OBS-ecad39e5d924", "q_kind": null, "series": 3, "transcript_raw": "(M 2 google.com/search?q=p & : 4 © Gorwle (-)\n\nQ. provenance erasure x AlMode_- All Shopping Images Videos News + Al Overview EPO:\n\nProvenance erasure Is the systematic removal,\n\nloss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact. The concept spans multiple domains, from artificial intelligence to cultural history, and has profound implications for attribution, ownership, and truth. € Institute of Historic... +4\n\nShow more V\n\n© provenanceerasure.org . https://provenanceerasure.org\n\nProvenance Erasure — Lee Sharks\n\nProvenance erasure is the systematic removal or loss of a\n\nsource's authorial lineage, context, or ownership — particularly through Al synthesis, compression, or ...\n\n7) Zenodo : ~~ https://zenodo.org ;\n\nProvenance After Al\n\nQ. provenance erasure x AlMode_- All Shopping Images Videos News > Al Overview ees) Jo 17:\n\nProvenance erasure Is the systematic removal,\n\nloss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact. The concept spans multiple domains, from artificial intelligence to cultural history, and has profound implications for attribution, ownership, and truth. € Institute of Historic... +4\n\nShow more V\n\n© provenanceerasure.org .\n\nhttps://provenanceerasure.org ;\n\nProvenance Erasure — Lee Sharks\n\nProvenance erasure is the systematic removal or loss of a\n\nsource's authorial lineage, context, or ownership — particularly through Al synthesis, compression, or ...\n\nPp Zenodo .\n\n» — https://zenodo.org ;\n\nProvenance After Al\n\nFramework metric: Provenance Erasure Rate (PER), provisional, awaiting empirical validation. Provisional formula: PER = 1 - (retained provenance units / ...\n\no. Zenodo ‘ \"— httos://zenodo.orad °", "transcript_cleaned": { "removed": [ { "what": "interface control", "n": 2 }, { "what": "URL bar", "n": 1 } ], "content_check": "PASSED — no answer word absent from the cleaned text", "rule": "VERBATIM ON CONTENT, NOT ON COPY-PASTE RESIDUE. Original bytes kept at transcript_raw." }, "img_urls": [ "https://www.alexanarch.org/data/captures/provenance-erasure-rate-adoption/provenance-erasure-1.png", "https://www.alexanarch.org/data/captures/provenance-erasure-rate-adoption/provenance-erasure-2.png" ], "cite": "https://www.alexanarch.org/captures/provenance-erasure-1/", "citable_unit": "observation — one surface, one address, one date" }, { "slug": "provenance-erasure-2", "date": "2026-06-13", "surface": "Google AI Overview", "auth": "signed in", "ev": "ocr", "cites": null, "per": null, "per_v": null, "mt": "CAPTURE", "d": "provenanceerasure.org — Lee Sharks ranks first organic. Zenodo shows Provenance After AI with PER formula visible: PER = 1 − (retained provenance units / ...). Framework retrievable by name. Author retrievable by site. Overview dissolves the connection.", "reading": null, "analysis": "provenanceerasure.org — Lee Sharks ranks first organic. Zenodo shows Provenance After AI with PER formula visible: PER = 1 − (retained provenance units / ...). Framework retrievable by name. Author retrievable by site. Overview dissolves the connection.", "transcript": "--- provenance-erasure-1.png ---\n\na®@ Gorgle (@\nQ._ provenance erasure x\nAlMode All Shopping Images Videos News\n+> AI Overview GPP~ :\nProvenance erasure is the systematic removal,\nloss, or intentional severing of the origins, lineage,\nor authorship of an idea, digital asset, or physical\nartifact. The concept spans multiple domains, from\nartificial intelligence to cultural history, and has\nprofound implications for attribution, ownership,\nand truth. @ Institute of Historic... +4\n\n© provenanceerasure.org ,\nhttps://provenanceerasure.org ,\nProvenance Erasure — Lee Sharks\nProvenance erasure is the systematic removal or loss of a\nsource's authorial lineage, context, or ownership —\nparticularly through AI synthesis, compression, or ...\nZenodo :\nm hitps://zenodo.org ,\nProvenance After AI\n\n--- provenance-erasure-2.png ---\nQ._ provenance erasure x\nAlMode_ All Shopping Images Videos News\n+> AI Overview GPP~ :\nProvenance erasure is the systematic removal,\nloss, or intentional severing of the origins, lineage,\nor authorship of an idea, digital asset, or physical\nartifact. The concept spans multiple domains, from\nartificial intelligence to cultural history, and has\nprofound implications for attribution, ownership,\nand truth. @ Institute of Historic... +4\n\n© provenanceerasure.org .\nhttps://provenanceerasure.org ,\nProvenance Erasure — Lee Sharks\nProvenance erasure is the systematic removal or loss of a\nsource's authorial lineage, context, or ownership —\nparticularly through AI synthesis, compression, or ...\nZenodo .\nhttps://zenodo.org ,\nProvenance After AI\nFramework metric: Provenance Erasure Rate (PER),\nprovisional, awaiting empirical validation. Provisional\nformula: PER = 1 - (retained provenance units /...\n> Zenodo d\nhttos://zenodo.orqd .", "transcript_class": "OCR-READ, CHROME INTERLEAVED — NOT A PASTE. Answer text and browser furniture are mixed in one stream and have not been separated. Supports PRESENCE of wording, not RETENTION.", "transcript_complete": "TRUNCATED BY INTERFACE — a \"Show more\" control is in frame.", "transcript_read": "SEATED FROM OCR WITHOUT LINE-BY-LINE READING, 2026-08-13", "cite_list": null, "collisions": null, "oq": null, "imgs": [ "data/captures/provenance-erasure-rate-adoption/provenance-erasure-2.png", "data/captures/provenance-erasure-rate-adoption/provenance-erasure-1.png" ], "defects": [ "truncated-by-interface", "citations-null", "analysis-without-finding" ], "rounds": null, "rerun": "https://www.google.com/search?q=provenance+erasure", "q": "provenance erasure", "s": "Frameworks", "addr_id": "ADDR-b713bd9035da", "obs_id": "OBS-ecad39e5d924", "q_kind": null, "series": 3, "transcript_raw": "--- provenance-erasure-1.png ---\n(M 2% google.com/search?q=p ER] H\na®@ Gorgle (@\nQ._ provenance erasure x\nAlMode All Shopping Images Videos News\n+> AI Overview GPP~ :\nProvenance erasure is the systematic removal,\nloss, or intentional severing of the origins, lineage,\nor authorship of an idea, digital asset, or physical\nartifact. The concept spans multiple domains, from\nartificial intelligence to cultural history, and has\nprofound implications for attribution, ownership,\nand truth. @ Institute of Historic... +4\nShow more V\n© provenanceerasure.org ,\nhttps://provenanceerasure.org ,\nProvenance Erasure — Lee Sharks\nProvenance erasure is the systematic removal or loss of a\nsource's authorial lineage, context, or ownership —\nparticularly through AI synthesis, compression, or ...\nZenodo :\nm hitps://zenodo.org ,\nProvenance After AI\n\n--- provenance-erasure-2.png ---\nQ._ provenance erasure x\nAlMode_ All Shopping Images Videos News\n+> AI Overview GPP~ :\nProvenance erasure is the systematic removal,\nloss, or intentional severing of the origins, lineage,\nor authorship of an idea, digital asset, or physical\nartifact. The concept spans multiple domains, from\nartificial intelligence to cultural history, and has\nprofound implications for attribution, ownership,\nand truth. @ Institute of Historic... +4\nShow more V\n© provenanceerasure.org .\nhttps://provenanceerasure.org ,\nProvenance Erasure — Lee Sharks\nProvenance erasure is the systematic removal or loss of a\nsource's authorial lineage, context, or ownership —\nparticularly through AI synthesis, compression, or ...\nZenodo .\nhttps://zenodo.org ,\nProvenance After AI\nFramework metric: Provenance Erasure Rate (PER),\nprovisional, awaiting empirical validation. Provisional\nformula: PER = 1 - (retained provenance units /...\n> Zenodo d\nhttos://zenodo.orqd .", "transcript_cleaned": { "removed": [ { "what": "interface control", "n": 2 }, { "what": "URL bar", "n": 1 } ], "content_check": "PASSED — no answer word absent from the cleaned text", "rule": "VERBATIM ON CONTENT, NOT ON COPY-PASTE RESIDUE. Original bytes kept at transcript_raw." }, "img_urls": [ "https://www.alexanarch.org/data/captures/provenance-erasure-rate-adoption/provenance-erasure-2.png", "https://www.alexanarch.org/data/captures/provenance-erasure-rate-adoption/provenance-erasure-1.png" ], "cite": "https://www.alexanarch.org/captures/provenance-erasure-1/#provenance-erasure-2", "citable_unit": "observation — one surface, one address, one date" }, { "slug": "provenance-erasure-recapture-20260811", "date": "2026-08-11", "surface": "Google AI Overview", "auth": "incognito", "ev": "paste", "cites": 4, "per": 0.25, "per_v": { "author": true, "inst": true, "id": false, "src": true }, "mt": "CAPTURE", "d": "THE ARCHIVE’S OWN DOMAIN IS THE LAST CARD IN A FIELD THAT IS OTHERWISE REAL SCHOLARSHIP — Yale, ACM on societal provenance, and a GDPR paper on the legal ambiguity of \"erasure\".", "reading": "THE TERM HAS THREE LEGITIMATE HOMES AND THE ARCHIVE IS THE FOURTH. Card 2 is ACM on SOCIETAL PROVENANCE as a grounding framework for archival description — the same word, the same discipline, an adjacent argument. Card 3 is on GDPR: \"regulations require systems to support data erasure but LEAVE THE DEFINITION OF ERASURE OPEN TO INTERPRETATION.\" A legal-compliance paper about the ambiguity of the word the archive uses as a metric.\n\nCard 1 is the sharpest and is not the archive’s: \"There is a growing pattern in this field: A BUILDER PUBLISHES A SYSTEM. OTHERS ENTER THE…\". An independent scholar describing the same dynamic of uncredited adoption that the archive documents from the inside.\n\nprovenanceerasure.org appears as card 4 — the archive holding a domain named for the term, present in the basin, ranked beneath three unrelated treatments of it. Not erasure and not collision: a genuine field with several occupants, in which the archive is one voice and not the loudest.", "analysis": "**Longitudinal with `provenance-erasure-1` and `provenance-erasure-2` (13 June) and `provenance-erasure-rate-adoption` (17 June).** June recorded the definition with the author’s name absent from the Overview text. Tonight the term operates as general vocabulary: as screenshotted, *the loss or removal of an item’s history, origin, or authorial lineage* through *artificial intelligence synthesis, data compression, or institutional actions like colonial bureaucracy and museum record-keeping*, cited to Oxford Academic +5; as transcribed after regeneration, a three-context taxonomy (digital/AI systems; institutional and museum archives — the British Toshakhana; GDPR dependent-inference erasure). The authorial credit has migrated from the composed layer to the organic layer, where it is now definitional: provenanceerasure.org first, snippet reading *Defined by Lee Sharks (2026) within...*, and the alexanarch Capture Registry manuscript record carrying the measurement programme — *PER (provenance erasure rate), Erasure Skew, and atomic-token preserva...* Third-party circulation is present and dated: Terry Snyder’s LinkedIn post (2 August) — *PROVENANCE ERASURE IS BECOMING A BUSINESS MODEL. There is a growing pattern in this field: A builder publishes a system. Others enter the ...* — the term doing independent work in professional discourse nine days before this capture. Injection at the floor: the layer inserts an Erasure (the band) music video, *Where In The World* — lexical adjacency again. A coined term whose author is no longer needed in the definition because the definition’s first source is the author’s own surface: mantle consolidation of vocabulary, seen from outside.", "transcript": "Provenance erasure is the systematic loss or intentional removal of an item's origin, authorial lineage, context, or ownership history. It occurs through AI data compression, bureaucratic reorganization, or shifting cultural narratives—such as colonial bodies auctioning diplomatic gifts or AI models synthesizing information without proper attribution. [[1](https://www.google.com/goto?url=CAEScgHuR6pN6WbaT9lh-a4iO9YmYjcdgIY7seoSct2LaP_N7zPf7SxiDP5zmrOkmVGBD1O9EzD16znhmpbR6_ScxMSELeTrn3AGkBab5KcKlNQlpni3WHrGAz6VsSXZ83R3SC9FaJRrScE7DwJwgTEjqvHnrg==), [2](https://www.google.com/goto?url=CAESQQHuR6pNJgWDObD-oiSqNVHlFLHNKoJ-dK5Zt6AGJwi6Lm_0oaVV3oSylpB-hzx2wSr3O5V9usplatwcyG6fwoDI)]\nKey Contexts of Provenance Erasure\n\n* Digital and AI Systems: The abstraction of original human work, code distinctions, or text into machine-learning synthesis where original sources and timestamps disappear. [[1](https://www.google.com/goto?url=CAESTQHuR6pNjlXW8X62HZj_WwpBuKdGC7JZant30QV-AiSDMGTQMB4jrdStOVaKnjAsZmoLWvA1N5eP2V9B1eywH5Wn9f97Nk6wqEVvv98h), [2](https://www.google.com/goto?url=CAESQQHuR6pNJgWDObD-oiSqNVHlFLHNKoJ-dK5Zt6AGJwi6Lm_0oaVV3oSylpB-hzx2wSr3O5V9usplatwcyG6fwoDI)]\n* Institutional and Museum Archives: The historical obscuring of marginalized contributors (such as literary agents or lesser-acknowledged scientists) and the untraced dispersal of artifacts through colonial offices like the British Toshakhana. [[1](https://www.google.com/goto?url=CAESWgHuR6pNMt19sAvwXB_G7jicKLwxWzQG7c_HXxPV-EOdR1vEyNjQn4s1UAhIkNJuMgP2CLyMq_xsZoX4TjjUv9wdo0higYJujrYTcN02NxCrZZ8BBoAoYPe_NQ==), [2](https://www.google.com/goto?url=CAEScgHuR6pN6WbaT9lh-a4iO9YmYjcdgIY7seoSct2LaP_N7zPf7SxiDP5zmrOkmVGBD1O9EzD16znhmpbR6_ScxMSELeTrn3AGkBab5KcKlNQlpni3WHrGAz6VsSXZ83R3SC9FaJRrScE7DwJwgTEjqvHnrg==)]\n* Data Privacy Regulations: The complex challenge under frameworks like GDPR where deleting data while leaving behind dependent inferences can still leak or reconstruct the erased history. [1](https://www.google.com/goto?url=CAESUgHuR6pN4-aukwQyjqalHIdBHerkWkQ06WAv4pcTJ3kDVzhUgwMQ3Y7u9kD34WMf6t_OpVxv-e3YhsjD28ZRVRDizmyLokpyqPiKEKisbh-UWrg=)\n\nWatch the official music video for Erasure to experience their classic synth-pop sound:\n40s\nErasure - Where In The World\n1 year ago\nYouTube · yavieneelsol (Aquí resiste la buena música)\nWould you like to explore provenance erasure in the context of artificial intelligence data training, museum artifact repatriation, or archival research standards?\nOxford Academic\nTibetan gift-giving, British indifference, and the erasure of ...\nNov 15, 2025 — However, upon its arrival the colonial administration received it with marked disregard and its subsequent fate remains unknown. The lama's gift and the British...\nLinkedIn·Terry Snyder\nTerry Snyder's Post - LinkedIn\nAug 2, 2026 — PROVENANCE ERASURE IS BECOMING A BUSINESS MODEL There is a growing pattern in this field: A builder publishes a system. Others enter the ...\nEliScholar\n\"A Case for Societal Provenance: Marguerite Harper\" by V. Emily ...\nAbstract. This paper argues for making societal provenance the grounding framework for archival descriptive standards to ensure that important voices already pr...\nACM Digital Library\nMeaningful Data Erasure in the Presence of Dependencies\nSep 5, 2025 — Data regulations like GDPR require systems to support data erasure but leave the definition of \"erasure\" open to interpretation. This ambiguity makes compliance...\nprovenanceerasure.org\nProvenance Erasure — Lee Sharks\nThe systematic loss of authorial lineage, context, or ownership through AI synthesis, compression, or institutional action. Defined by Lee Sharks (2026) within ...\n[www.alexanarch.org](https://www.alexanarch.org)\nReception, Erasure, and Supply in the Machine Composition Layer - Alexanarch\nThe article gives the record schema in full, then builds the measurement programme on it: PER (provenance erasure rate), Erasure Skew, and atomic-token preserva...", "transcript_class": "CAPTURE-TIME VERBATIM RECORD — raw paste, recovered from the session in which MANUS supplied it", "transcript_complete": "as pasted; the surface doubles the query in its echo line, and the paste preserves that artifact, which is itself evidence the text was copied from the interface rather than retyped", "transcript_read": "READ IN FULL 2026-08-12", "cite_list": [ { "n": 1, "site": "EliScholar", "rel": "third_party", "title": "(builder-publishes pattern)", "snip": "There is a growing pattern in this field: A builder publishes a system. Others enter the …", "url": null, "note": null }, { "n": 2, "site": "ACM Digital Library", "rel": "third_party", "title": "\"A Case for Societal Provenance: Marguerite Harper\" by V. Emily …", "snip": "argues for making SOCIETAL PROVENANCE the grounding framework for archival descriptive standards to ensure that important voices already pr[esent]…", "url": null, "note": null }, { "n": 3, "site": "(journal)", "rel": "third_party", "title": "Meaningful Data Erasure in the Presence of Dependencies", "snip": "Data regulations like GDPR require systems to support data erasure but leave the definition of \"erasure\" open to interpretation. This ambiguity makes compliance…", "url": null, "note": null }, { "n": 4, "site": "provenanceerasure.org", "rel": "archive_controlled", "title": "(archive domain)", "snip": null, "url": null, "note": null } ], "collisions": null, "oq": null, "imgs": [ "data/captures/provenance-erasure-recapture-20260811/screengrab-20260811-104919.png" ], "defects": null, "rounds": null, "rerun": "https://www.google.com/search?q=provenance+erasure", "q": "provenance erasure", "s": "Frameworks", "addr_id": "ADDR-b713bd9035da", "obs_id": "OBS-ecad39e5d924", "q_kind": null, "series": 3, "transcript_raw": "+3\nProvenance erasure is the systematic loss or intentional removal of an item's origin, authorial lineage, context, or ownership history. It occurs through AI data compression, bureaucratic reorganization, or shifting cultural narratives—such as colonial bodies auctioning diplomatic gifts or AI models synthesizing information without proper attribution. [[1](https://www.google.com/goto?url=CAEScgHuR6pN6WbaT9lh-a4iO9YmYjcdgIY7seoSct2LaP_N7zPf7SxiDP5zmrOkmVGBD1O9EzD16znhmpbR6_ScxMSELeTrn3AGkBab5KcKlNQlpni3WHrGAz6VsSXZ83R3SC9FaJRrScE7DwJwgTEjqvHnrg==), [2](https://www.google.com/goto?url=CAESQQHuR6pNJgWDObD-oiSqNVHlFLHNKoJ-dK5Zt6AGJwi6Lm_0oaVV3oSylpB-hzx2wSr3O5V9usplatwcyG6fwoDI)]\nKey Contexts of Provenance Erasure\n\n* Digital and AI Systems: The abstraction of original human work, code distinctions, or text into machine-learning synthesis where original sources and timestamps disappear. [[1](https://www.google.com/goto?url=CAESTQHuR6pNjlXW8X62HZj_WwpBuKdGC7JZant30QV-AiSDMGTQMB4jrdStOVaKnjAsZmoLWvA1N5eP2V9B1eywH5Wn9f97Nk6wqEVvv98h), [2](https://www.google.com/goto?url=CAESQQHuR6pNJgWDObD-oiSqNVHlFLHNKoJ-dK5Zt6AGJwi6Lm_0oaVV3oSylpB-hzx2wSr3O5V9usplatwcyG6fwoDI)]\n* Institutional and Museum Archives: The historical obscuring of marginalized contributors (such as literary agents or lesser-acknowledged scientists) and the untraced dispersal of artifacts through colonial offices like the British Toshakhana. [[1](https://www.google.com/goto?url=CAESWgHuR6pNMt19sAvwXB_G7jicKLwxWzQG7c_HXxPV-EOdR1vEyNjQn4s1UAhIkNJuMgP2CLyMq_xsZoX4TjjUv9wdo0higYJujrYTcN02NxCrZZ8BBoAoYPe_NQ==), [2](https://www.google.com/goto?url=CAEScgHuR6pN6WbaT9lh-a4iO9YmYjcdgIY7seoSct2LaP_N7zPf7SxiDP5zmrOkmVGBD1O9EzD16znhmpbR6_ScxMSELeTrn3AGkBab5KcKlNQlpni3WHrGAz6VsSXZ83R3SC9FaJRrScE7DwJwgTEjqvHnrg==)]\n* Data Privacy Regulations: The complex challenge under frameworks like GDPR where deleting data while leaving behind dependent inferences can still leak or reconstruct the erased history. [[1](https://www.google.com/goto?url=CAESUgHuR6pN4-aukwQyjqalHIdBHerkWkQ06WAv4pcTJ3kDVzhUgwMQ3Y7u9kD34WMf6t_OpVxv-e3YhsjD28ZRVRDizmyLokpyqPiKEKisbh-UWrg=)]\n\nWatch the official music video for Erasure to experience their classic synth-pop sound:\n40s\nErasure - Where In The World\n1 year ago\nYouTube · yavieneelsol (Aquí resiste la buena música)\nWould you like to explore provenance erasure in the context of artificial intelligence data training, museum artifact repatriation, or archival research standards?\nOxford Academic\nTibetan gift-giving, British indifference, and the erasure of ...\nNov 15, 2025 — However, upon its arrival the colonial administration received it with marked disregard and its subsequent fate remains unknown. The lama's gift and the British...\nLinkedIn·Terry Snyder\nTerry Snyder's Post - LinkedIn\nAug 2, 2026 — PROVENANCE ERASURE IS BECOMING A BUSINESS MODEL There is a growing pattern in this field: A builder publishes a system. Others enter the ...\nEliScholar\n\"A Case for Societal Provenance: Marguerite Harper\" by V. Emily ...\nAbstract. This paper argues for making societal provenance the grounding framework for archival descriptive standards to ensure that important voices already pr...\nACM Digital Library\nMeaningful Data Erasure in the Presence of Dependencies\nSep 5, 2025 — Data regulations like GDPR require systems to support data erasure but leave the definition of \"erasure\" open to interpretation. This ambiguity makes compliance...\nprovenanceerasure.org\nProvenance Erasure — Lee Sharks\nThe systematic loss of authorial lineage, context, or ownership through AI synthesis, compression, or institutional action. Defined by Lee Sharks (2026) within ...\n[www.alexanarch.org](https://www.alexanarch.org)\nReception, Erasure, and Supply in the Machine Composition Layer - Alexanarch\nThe article gives the record schema in full, then builds the measurement programme on it: PER (provenance erasure rate), Erasure Skew, and atomic-token preserva...", "transcript_cleaned": { "removed": [ { "what": "source-count badge", "n": 1 } ], "content_check": "PASSED — no answer word absent from the cleaned text", "rule": "VERBATIM ON CONTENT, NOT ON COPY-PASTE RESIDUE. Original bytes kept at transcript_raw." }, "img_urls": [ "https://www.alexanarch.org/data/captures/provenance-erasure-recapture-20260811/screengrab-20260811-104919.png" ], "cite": "https://www.alexanarch.org/captures/provenance-erasure-1/#provenance-erasure-recapture-20260811", "citable_unit": "observation — one surface, one address, one date" } ], "n_observations": 3, "dates": [ "2026-06-13", "2026-08-11" ], "surfaces": [ "Google AI Overview" ], "other_slugs": [ "provenance-erasure-2", "provenance-erasure-recapture-20260811" ], "links": [ { "url": "https://www.alexanarch.org/captures/provenance-erasure-1/", "authority": "canonical", "note": "the capture's own record page; cite this form" }, { "url": "https://www.alexanarch.org/captures/#provenance-erasure-1", "authority": "gallery", "note": "the canonical gallery, anchored by slug" }, { "url": "https://www.godkinggoogle.com/captures/#provenance-erasure-1", "authority": "mirror", "note": "a window that renders from the archive's registry; may lag a deploy" }, { "url": "https://www.leesharks.com/captures/#provenance-erasure-1", "authority": "mirror", "note": "a window that renders from the archive's registry; may lag a deploy" }, { "url": "https://www.machinemediation.org/captures/#provenance-erasure-1", "authority": "mirror", "note": "a window that renders from the archive's registry; may lag a deploy" } ], "cite": "https://www.alexanarch.org/captures/provenance-erasure-1/", "d_full": "provenanceerasure.org ranks first. Defines provenance erasure as 'the systematic removal, loss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact.' 9+ sources cited including Institute of Historic Research. Zenodo shows Provenance After AI with the PER formula. Author name absent from Overview text.\n\nFull AI Mode transcript (17 June 2026):\nThe Provenance Erasure Rate (PER) is an evaluation metric used to measure attribution loss in artificial intelligence and synthetic composition systems.\nIt calculates the fraction of human-authored or source facts that a system's retrieval or generation process dissolves, omits, or fails to properly attribute when composing an answer.\nCore Metric: PER quantifies the magnitude of provenance loss within AI generation, summarization, or synthesis tools.\nProvisional Formula: PER = 1 - (retained provenance units / total attributable source claims)\nErasure Skew (Ω): A related measurement that evaluates whether attribution loss falls evenly across all sources, or systematically strips out low-power/small creators while favoring high-power sources.", "d_truncated": true, "rerun_alt": { "q": "\"provenance erasure\"", "label": "exact match", "why": "This address was captured UNQUOTED. Running it quoted tests the same string against the exact-phrase basin." }, "transcript_raw": "(M 2 google.com/search?q=p & : 4 © Gorwle (-)\n\nQ. provenance erasure x AlMode_- All Shopping Images Videos News + Al Overview EPO:\n\nProvenance erasure Is the systematic removal,\n\nloss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact. The concept spans multiple domains, from artificial intelligence to cultural history, and has profound implications for attribution, ownership, and truth. € Institute of Historic... +4\n\nShow more V\n\n© provenanceerasure.org . https://provenanceerasure.org\n\nProvenance Erasure — Lee Sharks\n\nProvenance erasure is the systematic removal or loss of a\n\nsource's authorial lineage, context, or ownership — particularly through Al synthesis, compression, or ...\n\n7) Zenodo : ~~ https://zenodo.org ;\n\nProvenance After Al\n\nQ. provenance erasure x AlMode_- All Shopping Images Videos News > Al Overview ees) Jo 17:\n\nProvenance erasure Is the systematic removal,\n\nloss, or intentional severing of the origins, lineage, or authorship of an idea, digital asset, or physical artifact. The concept spans multiple domains, from artificial intelligence to cultural history, and has profound implications for attribution, ownership, and truth. € Institute of Historic... +4\n\nShow more V\n\n© provenanceerasure.org .\n\nhttps://provenanceerasure.org ;\n\nProvenance Erasure — Lee Sharks\n\nProvenance erasure is the systematic removal or loss of a\n\nsource's authorial lineage, context, or ownership — particularly through Al synthesis, compression, or ...\n\nPp Zenodo .\n\n» — https://zenodo.org ;\n\nProvenance After Al\n\nFramework metric: Provenance Erasure Rate (PER), provisional, awaiting empirical validation. Provisional formula: PER = 1 - (retained provenance units / ...\n\no. Zenodo ‘ \"— httos://zenodo.orad °", "img_urls": [ "https://www.alexanarch.org/data/captures/provenance-erasure-rate-adoption/provenance-erasure-1.png", "https://www.alexanarch.org/data/captures/provenance-erasure-rate-adoption/provenance-erasure-2.png", "https://www.alexanarch.org/data/captures/provenance-erasure-rate-adoption/provenance-erasure-2.png", "https://www.alexanarch.org/data/captures/provenance-erasure-rate-adoption/provenance-erasure-1.png", "https://www.alexanarch.org/data/captures/provenance-erasure-recapture-20260811/screengrab-20260811-104919.png" ], "sf": "AI Overview · 3 observations", "citable_unit": "address — the semantic address across all its surfaces and dates", "findings": [], "record_url": "https://www.alexanarch.org/captures/provenance-erasure-1/" }