{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:BWMOJM2FBX3SUMUGSSURDHESXJ","short_pith_number":"pith:BWMOJM2F","canonical_record":{"source":{"id":"2210.10689","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-19T16:03:25Z","cross_cats_sorted":[],"title_canon_sha256":"78e3119ffeee6130eb13ac0167bdfe7a1c8a56a7c2f8d4d5d3cf4e4da1754789","abstract_canon_sha256":"d28a7cba56cd3355273d02dde6d2398bbc36ac22cc20ebdabf0e16322975148b"},"schema_version":"1.0"},"canonical_sha256":"0d98e4b3450df72a328694a9119c92ba4f5dfa2ec3ca435c06ad1a70ae11bf43","source":{"kind":"arxiv","id":"2210.10689","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.10689","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"arxiv_version","alias_value":"2210.10689v1","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.10689","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"pith_short_12","alias_value":"BWMOJM2FBX3S","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"pith_short_16","alias_value":"BWMOJM2FBX3SUMUG","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"pith_short_8","alias_value":"BWMOJM2F","created_at":"2026-07-05T05:08:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:BWMOJM2FBX3SUMUGSSURDHESXJ","target":"record","payload":{"canonical_record":{"source":{"id":"2210.10689","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-19T16:03:25Z","cross_cats_sorted":[],"title_canon_sha256":"78e3119ffeee6130eb13ac0167bdfe7a1c8a56a7c2f8d4d5d3cf4e4da1754789","abstract_canon_sha256":"d28a7cba56cd3355273d02dde6d2398bbc36ac22cc20ebdabf0e16322975148b"},"schema_version":"1.0"},"canonical_sha256":"0d98e4b3450df72a328694a9119c92ba4f5dfa2ec3ca435c06ad1a70ae11bf43","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:08:22.797175Z","signature_b64":"N/YeWg38KP+5pfTN0WpLcAwAH81g3F+Hbx0SU9b1xlaLdZkP+eujCbMB/wHCmkRA2vmWluOLTWNyEwudJTiqCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0d98e4b3450df72a328694a9119c92ba4f5dfa2ec3ca435c06ad1a70ae11bf43","last_reissued_at":"2026-07-05T05:08:22.796716Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:08:22.796716Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.10689","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":"2026-07-05T05:08:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XZ/SbX+MKCuQ21EY5RuZ1AJtd1wR41yRUQIEwuOTXfml2I16a9BdGoBSPkY4/uXd28Xpem8XodHv8o6+WZ3QDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:27:45.646294Z"},"content_sha256":"1fad6b45d786389bce47abbff7071e683921156186929b28c86a7e1b8838cebb","schema_version":"1.0","event_id":"sha256:1fad6b45d786389bce47abbff7071e683921156186929b28c86a7e1b8838cebb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:BWMOJM2FBX3SUMUGSSURDHESXJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Procedural Fairness: Uncovering Biases in How a Toxic Language Classifier Uses Sentiment Information","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Esma Balk{\\i}r, Isar Nejadgholi, Kathleen C. Fraser, Svetlana Kiritchenko","submitted_at":"2022-10-19T16:03:25Z","abstract_excerpt":"Previous works on the fairness of toxic language classifiers compare the output of models with different identity terms as input features but do not consider the impact of other important concepts present in the context. Here, besides identity terms, we take into account high-level latent features learned by the classifier and investigate the interaction between these features and identity terms. For a multi-class toxic language classifier, we leverage a concept-based explanation framework to calculate the sensitivity of the model to the concept of sentiment, which has been used before as a sa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.10689","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/2210.10689/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":"2026-07-05T05:08:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g9CQ7OjHJI7iQ/ZiJnwoCS6MBPhIUBO/fRknh7rivjNWZHKKyGdffISEEbRTtxrnTsEgKOuQKJDmkDS5jISICA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:27:45.646882Z"},"content_sha256":"2bb8e5cce3526facac0eccfcace9bff60d5b1ececb2a504a92f9cd71b4fa004b","schema_version":"1.0","event_id":"sha256:2bb8e5cce3526facac0eccfcace9bff60d5b1ececb2a504a92f9cd71b4fa004b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BWMOJM2FBX3SUMUGSSURDHESXJ/bundle.json","state_url":"https://pith.science/pith/BWMOJM2FBX3SUMUGSSURDHESXJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BWMOJM2FBX3SUMUGSSURDHESXJ/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":"2026-08-10T09:27:45Z","links":{"resolver":"https://pith.science/pith/BWMOJM2FBX3SUMUGSSURDHESXJ","bundle":"https://pith.science/pith/BWMOJM2FBX3SUMUGSSURDHESXJ/bundle.json","state":"https://pith.science/pith/BWMOJM2FBX3SUMUGSSURDHESXJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BWMOJM2FBX3SUMUGSSURDHESXJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:BWMOJM2FBX3SUMUGSSURDHESXJ","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":"d28a7cba56cd3355273d02dde6d2398bbc36ac22cc20ebdabf0e16322975148b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-19T16:03:25Z","title_canon_sha256":"78e3119ffeee6130eb13ac0167bdfe7a1c8a56a7c2f8d4d5d3cf4e4da1754789"},"schema_version":"1.0","source":{"id":"2210.10689","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.10689","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"arxiv_version","alias_value":"2210.10689v1","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.10689","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"pith_short_12","alias_value":"BWMOJM2FBX3S","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"pith_short_16","alias_value":"BWMOJM2FBX3SUMUG","created_at":"2026-07-05T05:08:22Z"},{"alias_kind":"pith_short_8","alias_value":"BWMOJM2F","created_at":"2026-07-05T05:08:22Z"}],"graph_snapshots":[{"event_id":"sha256:2bb8e5cce3526facac0eccfcace9bff60d5b1ececb2a504a92f9cd71b4fa004b","target":"graph","created_at":"2026-07-05T05:08:22Z","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/2210.10689/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Previous works on the fairness of toxic language classifiers compare the output of models with different identity terms as input features but do not consider the impact of other important concepts present in the context. Here, besides identity terms, we take into account high-level latent features learned by the classifier and investigate the interaction between these features and identity terms. For a multi-class toxic language classifier, we leverage a concept-based explanation framework to calculate the sensitivity of the model to the concept of sentiment, which has been used before as a sa","authors_text":"Esma Balk{\\i}r, Isar Nejadgholi, Kathleen C. Fraser, Svetlana Kiritchenko","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-19T16:03:25Z","title":"Towards Procedural Fairness: Uncovering Biases in How a Toxic Language Classifier Uses Sentiment Information"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.10689","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":"sha256:1fad6b45d786389bce47abbff7071e683921156186929b28c86a7e1b8838cebb","target":"record","created_at":"2026-07-05T05:08:22Z","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":"d28a7cba56cd3355273d02dde6d2398bbc36ac22cc20ebdabf0e16322975148b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-19T16:03:25Z","title_canon_sha256":"78e3119ffeee6130eb13ac0167bdfe7a1c8a56a7c2f8d4d5d3cf4e4da1754789"},"schema_version":"1.0","source":{"id":"2210.10689","kind":"arxiv","version":1}},"canonical_sha256":"0d98e4b3450df72a328694a9119c92ba4f5dfa2ec3ca435c06ad1a70ae11bf43","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0d98e4b3450df72a328694a9119c92ba4f5dfa2ec3ca435c06ad1a70ae11bf43","first_computed_at":"2026-07-05T05:08:22.796716Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:08:22.796716Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N/YeWg38KP+5pfTN0WpLcAwAH81g3F+Hbx0SU9b1xlaLdZkP+eujCbMB/wHCmkRA2vmWluOLTWNyEwudJTiqCg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:08:22.797175Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.10689","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1fad6b45d786389bce47abbff7071e683921156186929b28c86a7e1b8838cebb","sha256:2bb8e5cce3526facac0eccfcace9bff60d5b1ececb2a504a92f9cd71b4fa004b"],"state_sha256":"81e3137df968b34725f5048a76e76ccc0ea66ac517c54b89a1ea1876381b1893"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RcDm3ldx1ZQS8XhoVufd86BlOl45LAn8+2Qrw3c1GgAXSj6MXnGCoDwA5X0osS8Lp0a2ws2BD7R1YCh8IbjfDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T09:27:45.652059Z","bundle_sha256":"78e846141a9dc720dccd72a5c17c9e29490469d21707082d4658f7d23b95b021"}}