{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LJF4T6TFMH7A7SO63ONJXG2IQ3","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":"8e7d563400f5e7dfede3d80b088964bc78f5f6c2b373c086705275880525b650","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-03-15T06:36:58Z","title_canon_sha256":"e30eb3c8e85c3a72968f0386efc2d5bd3c8d772737bd4d8bcce0d6879c7c622c"},"schema_version":"1.0","source":{"id":"1703.04957","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.04957","created_at":"2026-05-18T00:48:38Z"},{"alias_kind":"arxiv_version","alias_value":"1703.04957v1","created_at":"2026-05-18T00:48:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.04957","created_at":"2026-05-18T00:48:38Z"},{"alias_kind":"pith_short_12","alias_value":"LJF4T6TFMH7A","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LJF4T6TFMH7A7SO6","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LJF4T6TF","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:f61fc156db8150eb9639147cc2de8e5b6a90e5e9f8158ccf47a96becdac66c99","target":"graph","created_at":"2026-05-18T00:48:38Z","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"},"paper":{"abstract_excerpt":"Predictive modeling is increasingly being employed to assist human decision-makers. One purported advantage of replacing or augmenting human judgment with computer models in high stakes settings-- such as sentencing, hiring, policing, college admissions, and parole decisions-- is the perceived \"neutrality\" of computers. It is argued that because computer models do not hold personal prejudice, the predictions they produce will be equally free from prejudice. There is growing recognition that employing algorithms does not remove the potential for bias, and can even amplify it if the training dat","authors_text":"James E. Johndrow, Kristian Lum","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-03-15T06:36:58Z","title":"An algorithm for removing sensitive information: application to race-independent recidivism prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.04957","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":"sha256:18033b92fd2a08a525cd1c702e6cba37601964fa3031cffc5c379ec4bc6551a1","target":"record","created_at":"2026-05-18T00:48:38Z","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":"8e7d563400f5e7dfede3d80b088964bc78f5f6c2b373c086705275880525b650","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2017-03-15T06:36:58Z","title_canon_sha256":"e30eb3c8e85c3a72968f0386efc2d5bd3c8d772737bd4d8bcce0d6879c7c622c"},"schema_version":"1.0","source":{"id":"1703.04957","kind":"arxiv","version":1}},"canonical_sha256":"5a4bc9fa6561fe0fc9dedb9a9b9b4886e595492765e8f9d8d326a10a2f85d1ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a4bc9fa6561fe0fc9dedb9a9b9b4886e595492765e8f9d8d326a10a2f85d1ac","first_computed_at":"2026-05-18T00:48:38.726992Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:48:38.726992Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dBSlC1t1Y+RHPYW/4sO5DPL59YDoyaH7p8rQJ1DFm+le9+GTnoYd/nszsFDqao1t6guAN58a9Qm2RUIPDVDvAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:48:38.727526Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.04957","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18033b92fd2a08a525cd1c702e6cba37601964fa3031cffc5c379ec4bc6551a1","sha256:f61fc156db8150eb9639147cc2de8e5b6a90e5e9f8158ccf47a96becdac66c99"],"state_sha256":"370543687f8285ee383cb8f4f2c0320d81a32e1417c2d59c068a08d8fae8050c"}