{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:FEBWAIN3MGO4PACDWA3RT2XKPH","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":"a5d4bcaacb24c719159026dbd1a81b598b4dbd57bcd456235623f1c9d292c32f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2025-08-10T23:55:16Z","title_canon_sha256":"46d3c8331656e79dff49b5d233f3ddf41858e310cd93a85fc87f746b92132fa0"},"schema_version":"1.0","source":{"id":"2508.08337","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.08337","created_at":"2026-06-02T01:03:33Z"},{"alias_kind":"arxiv_version","alias_value":"2508.08337v3","created_at":"2026-06-02T01:03:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.08337","created_at":"2026-06-02T01:03:33Z"},{"alias_kind":"pith_short_12","alias_value":"FEBWAIN3MGO4","created_at":"2026-06-02T01:03:33Z"},{"alias_kind":"pith_short_16","alias_value":"FEBWAIN3MGO4PACD","created_at":"2026-06-02T01:03:33Z"},{"alias_kind":"pith_short_8","alias_value":"FEBWAIN3","created_at":"2026-06-02T01:03:33Z"}],"graph_snapshots":[{"event_id":"sha256:a747cc07c8047af9bfe6973f382ff1ef3a39f8760960345f0851eb7cc9d0ba3a","target":"graph","created_at":"2026-06-02T01:03:33Z","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/2508.08337/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Algorithmic fairness research has largely framed unfairness as discrimination along sensitive attributes. However, this approach limits visibility into unfairness as structural injustice instantiated through social determinants, which are contextual variables that shape attributes and outcomes without pertaining to specific individuals. This position paper argues that the field should quantify structural injustice via social determinants, beyond sensitive attributes. Drawing on cross-disciplinary insights, we argue that prevailing technical paradigms fail to adequately capture unfairness as st","authors_text":"Alex John London, Atoosa Kasirzadeh, Kun Zhang, Peter Spirtes, Sanmi Koyejo, Sarah Stewart de Ramirez, Zeyu Tang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2025-08-10T23:55:16Z","title":"Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.08337","kind":"arxiv","version":3},"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":"sha256:666dc71b7b243d15b40e459f980dcd9e26ae3f6f21b205aa837dc3e05488acfe","target":"record","created_at":"2026-06-02T01:03:33Z","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":"a5d4bcaacb24c719159026dbd1a81b598b4dbd57bcd456235623f1c9d292c32f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2025-08-10T23:55:16Z","title_canon_sha256":"46d3c8331656e79dff49b5d233f3ddf41858e310cd93a85fc87f746b92132fa0"},"schema_version":"1.0","source":{"id":"2508.08337","kind":"arxiv","version":3}},"canonical_sha256":"29036021bb619dc78043b03719eaea79d69a19922f479de250db815e8dfe00c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"29036021bb619dc78043b03719eaea79d69a19922f479de250db815e8dfe00c1","first_computed_at":"2026-06-02T01:03:33.165527Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-02T01:03:33.165527Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1wQtBAWVWX0nLtoAfCRAI21mH4HKCcgEFrRagplICF4jPomcQmytvVEgv7m8/SFL5m2FqGo4GB93ln18UNg7Dg==","signature_status":"signed_v1","signed_at":"2026-06-02T01:03:33.166147Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.08337","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:666dc71b7b243d15b40e459f980dcd9e26ae3f6f21b205aa837dc3e05488acfe","sha256:a747cc07c8047af9bfe6973f382ff1ef3a39f8760960345f0851eb7cc9d0ba3a"],"state_sha256":"9072218e3a70a25ca62c366910b9b99f27bc225f6b496822ad174c00a7f8783f"}