{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:HKDIF5TNNXKQ5A4LKJNWM5HK22","short_pith_number":"pith:HKDIF5TN","canonical_record":{"source":{"id":"2212.11672","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-20T18:45:12Z","cross_cats_sorted":[],"title_canon_sha256":"56ab1774a34c3a150a19188b0f0b7694868bc8b62cfae33303c7e0d22ff119a5","abstract_canon_sha256":"78bfeda23a9aff9f4d6015a746403586fde47bdc58a5be60940b2b09328162a6"},"schema_version":"1.0"},"canonical_sha256":"3a8682f66d6dd50e838b525b6674ead6b59dee68772076060be1220dbb7a9564","source":{"kind":"arxiv","id":"2212.11672","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.11672","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"arxiv_version","alias_value":"2212.11672v1","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.11672","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"pith_short_12","alias_value":"HKDIF5TNNXKQ","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"pith_short_16","alias_value":"HKDIF5TNNXKQ5A4L","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"pith_short_8","alias_value":"HKDIF5TN","created_at":"2026-07-05T08:45:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:HKDIF5TNNXKQ5A4LKJNWM5HK22","target":"record","payload":{"canonical_record":{"source":{"id":"2212.11672","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-20T18:45:12Z","cross_cats_sorted":[],"title_canon_sha256":"56ab1774a34c3a150a19188b0f0b7694868bc8b62cfae33303c7e0d22ff119a5","abstract_canon_sha256":"78bfeda23a9aff9f4d6015a746403586fde47bdc58a5be60940b2b09328162a6"},"schema_version":"1.0"},"canonical_sha256":"3a8682f66d6dd50e838b525b6674ead6b59dee68772076060be1220dbb7a9564","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:45:10.559937Z","signature_b64":"tRn8fXkY6M36y/2ZLvQOSy4SDu9Ow3EIxfANJjd0fSAJFASsy4Eo2hx2WcEv3mfmq/BbRm+mp8S97BhLcd2wAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a8682f66d6dd50e838b525b6674ead6b59dee68772076060be1220dbb7a9564","last_reissued_at":"2026-07-05T08:45:10.559480Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:45:10.559480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.11672","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:45:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mNzFptV1/MERmk0ceovIbUO/Ia06WrxYCaJ1O79XpbmWbqYJdyE8r8yhwfCoQbEuficPxWryyGCpHeSk6FBQCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T20:49:23.087385Z"},"content_sha256":"62b3100633093e3f12a3d53009904191df62fabdd7c63f3ab70bd2539403defe","schema_version":"1.0","event_id":"sha256:62b3100633093e3f12a3d53009904191df62fabdd7c63f3ab70bd2539403defe"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:HKDIF5TNNXKQ5A4LKJNWM5HK22","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Trustworthy Social Bias Measurement","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Percy Liang, Rishi Bommasani","submitted_at":"2022-12-20T18:45:12Z","abstract_excerpt":"How do we design measures of social bias that we trust? While prior work has introduced several measures, no measure has gained widespread trust: instead, mounting evidence argues we should distrust these measures. In this work, we design bias measures that warrant trust based on the cross-disciplinary theory of measurement modeling. To combat the frequently fuzzy treatment of social bias in NLP, we explicitly define social bias, grounded in principles drawn from social science research. We operationalize our definition by proposing a general bias measurement framework DivDist, which we use to"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.11672","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2212.11672/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:45:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"psd1aqGQ7YwN48QXKv1KmSsXDcFc3A52kVvLBqf6GJy2EtI/wmDfnUbMollKkJWsdwh6QIDqb5nITvPyPaEbAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T20:49:23.087794Z"},"content_sha256":"ab62f2ff68f547cabb5ea63d0e65fd34b95fb96e5f4e7eaed9b2931f158a7284","schema_version":"1.0","event_id":"sha256:ab62f2ff68f547cabb5ea63d0e65fd34b95fb96e5f4e7eaed9b2931f158a7284"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HKDIF5TNNXKQ5A4LKJNWM5HK22/bundle.json","state_url":"https://pith.science/pith/HKDIF5TNNXKQ5A4LKJNWM5HK22/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HKDIF5TNNXKQ5A4LKJNWM5HK22/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-22T20:49:23Z","links":{"resolver":"https://pith.science/pith/HKDIF5TNNXKQ5A4LKJNWM5HK22","bundle":"https://pith.science/pith/HKDIF5TNNXKQ5A4LKJNWM5HK22/bundle.json","state":"https://pith.science/pith/HKDIF5TNNXKQ5A4LKJNWM5HK22/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HKDIF5TNNXKQ5A4LKJNWM5HK22/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:HKDIF5TNNXKQ5A4LKJNWM5HK22","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"78bfeda23a9aff9f4d6015a746403586fde47bdc58a5be60940b2b09328162a6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-20T18:45:12Z","title_canon_sha256":"56ab1774a34c3a150a19188b0f0b7694868bc8b62cfae33303c7e0d22ff119a5"},"schema_version":"1.0","source":{"id":"2212.11672","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.11672","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"arxiv_version","alias_value":"2212.11672v1","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.11672","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"pith_short_12","alias_value":"HKDIF5TNNXKQ","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"pith_short_16","alias_value":"HKDIF5TNNXKQ5A4L","created_at":"2026-07-05T08:45:10Z"},{"alias_kind":"pith_short_8","alias_value":"HKDIF5TN","created_at":"2026-07-05T08:45:10Z"}],"graph_snapshots":[{"event_id":"sha256:ab62f2ff68f547cabb5ea63d0e65fd34b95fb96e5f4e7eaed9b2931f158a7284","target":"graph","created_at":"2026-07-05T08:45:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2212.11672/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"How do we design measures of social bias that we trust? While prior work has introduced several measures, no measure has gained widespread trust: instead, mounting evidence argues we should distrust these measures. In this work, we design bias measures that warrant trust based on the cross-disciplinary theory of measurement modeling. To combat the frequently fuzzy treatment of social bias in NLP, we explicitly define social bias, grounded in principles drawn from social science research. We operationalize our definition by proposing a general bias measurement framework DivDist, which we use to","authors_text":"Percy Liang, Rishi Bommasani","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-20T18:45:12Z","title":"Trustworthy Social Bias Measurement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.11672","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:62b3100633093e3f12a3d53009904191df62fabdd7c63f3ab70bd2539403defe","target":"record","created_at":"2026-07-05T08:45:10Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"78bfeda23a9aff9f4d6015a746403586fde47bdc58a5be60940b2b09328162a6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-20T18:45:12Z","title_canon_sha256":"56ab1774a34c3a150a19188b0f0b7694868bc8b62cfae33303c7e0d22ff119a5"},"schema_version":"1.0","source":{"id":"2212.11672","kind":"arxiv","version":1}},"canonical_sha256":"3a8682f66d6dd50e838b525b6674ead6b59dee68772076060be1220dbb7a9564","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3a8682f66d6dd50e838b525b6674ead6b59dee68772076060be1220dbb7a9564","first_computed_at":"2026-07-05T08:45:10.559480Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:45:10.559480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tRn8fXkY6M36y/2ZLvQOSy4SDu9Ow3EIxfANJjd0fSAJFASsy4Eo2hx2WcEv3mfmq/BbRm+mp8S97BhLcd2wAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:45:10.559937Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.11672","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:62b3100633093e3f12a3d53009904191df62fabdd7c63f3ab70bd2539403defe","sha256:ab62f2ff68f547cabb5ea63d0e65fd34b95fb96e5f4e7eaed9b2931f158a7284"],"state_sha256":"d10543ddeb19e6df52af04a3644639f77fb82b40ea99e7634f390cb102552bcb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wrPF8vTzt68zBC3JppZ/ZkYEskZ8d9wa26x8l95mIPDMXehzf+SU8f54QPGirw6H9ofUoGE94QVhgScyLpR6Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T20:49:23.090502Z","bundle_sha256":"b7396a03eac6e276e6761f33d6cabecd76a3e0bd107d0fb9a244916e9e34bb06"}}