{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:VLR5LVSIYELJIEO6CL2BBKRKYA","short_pith_number":"pith:VLR5LVSI","schema_version":"1.0","canonical_sha256":"aae3d5d648c1169411de12f410aa2ac00bb4fc1bd96dc3a3b942f0aaa28dbdab","source":{"kind":"arxiv","id":"2408.08471","version":2},"attestation_state":"computed","paper":{"title":"Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CY"],"primary_cat":"cs.CR","authors_text":"Ferdinando Fioretto, Joonhyuk Ko, Juba Ziani, Matt Williams, Saswat Das","submitted_at":"2024-08-16T01:13:36Z","abstract_excerpt":"Statistical agencies rely on sampling techniques to collect socio-demographic data crucial for policy-making and resource allocation. This paper shows that surveys of important societal relevance introduce sampling errors that unevenly impact group-level estimates, thereby compromising fairness in downstream decisions. To address these issues, this paper introduces an optimization approach modeled on real-world survey design processes, ensuring sampling costs are optimized while maintaining error margins within prescribed tolerances. Additionally, privacy-preserving methods used to determine s"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2408.08471","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-08-16T01:13:36Z","cross_cats_sorted":["cs.AI","cs.CY"],"title_canon_sha256":"35fcc8b93111a93158c11935ae78cb6efb61e93f8bdb2149b15f32f3f3ef67c6","abstract_canon_sha256":"68edfc792dd70deb27898764ed2e0d94f58ca185a27c8a15a9d315f1a331d00c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:02:50.492978Z","signature_b64":"JxGks8y9Bs8FIBCMdIR9KjK5xRmC6f3x9/DRLz4WulND/2s6sO8T3L2m5LR8lvl4K/R/gtbvDaNahZxjnvpJCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aae3d5d648c1169411de12f410aa2ac00bb4fc1bd96dc3a3b942f0aaa28dbdab","last_reissued_at":"2026-07-05T10:02:50.492337Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:02:50.492337Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CY"],"primary_cat":"cs.CR","authors_text":"Ferdinando Fioretto, Joonhyuk Ko, Juba Ziani, Matt Williams, Saswat Das","submitted_at":"2024-08-16T01:13:36Z","abstract_excerpt":"Statistical agencies rely on sampling techniques to collect socio-demographic data crucial for policy-making and resource allocation. This paper shows that surveys of important societal relevance introduce sampling errors that unevenly impact group-level estimates, thereby compromising fairness in downstream decisions. To address these issues, this paper introduces an optimization approach modeled on real-world survey design processes, ensuring sampling costs are optimized while maintaining error margins within prescribed tolerances. Additionally, privacy-preserving methods used to determine s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.08471","kind":"arxiv","version":2},"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/2408.08471/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2408.08471","created_at":"2026-07-05T10:02:50.492397+00:00"},{"alias_kind":"arxiv_version","alias_value":"2408.08471v2","created_at":"2026-07-05T10:02:50.492397+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.08471","created_at":"2026-07-05T10:02:50.492397+00:00"},{"alias_kind":"pith_short_12","alias_value":"VLR5LVSIYELJ","created_at":"2026-07-05T10:02:50.492397+00:00"},{"alias_kind":"pith_short_16","alias_value":"VLR5LVSIYELJIEO6","created_at":"2026-07-05T10:02:50.492397+00:00"},{"alias_kind":"pith_short_8","alias_value":"VLR5LVSI","created_at":"2026-07-05T10:02:50.492397+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VLR5LVSIYELJIEO6CL2BBKRKYA","json":"https://pith.science/pith/VLR5LVSIYELJIEO6CL2BBKRKYA.json","graph_json":"https://pith.science/api/pith-number/VLR5LVSIYELJIEO6CL2BBKRKYA/graph.json","events_json":"https://pith.science/api/pith-number/VLR5LVSIYELJIEO6CL2BBKRKYA/events.json","paper":"https://pith.science/paper/VLR5LVSI"},"agent_actions":{"view_html":"https://pith.science/pith/VLR5LVSIYELJIEO6CL2BBKRKYA","download_json":"https://pith.science/pith/VLR5LVSIYELJIEO6CL2BBKRKYA.json","view_paper":"https://pith.science/paper/VLR5LVSI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2408.08471&json=true","fetch_graph":"https://pith.science/api/pith-number/VLR5LVSIYELJIEO6CL2BBKRKYA/graph.json","fetch_events":"https://pith.science/api/pith-number/VLR5LVSIYELJIEO6CL2BBKRKYA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VLR5LVSIYELJIEO6CL2BBKRKYA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VLR5LVSIYELJIEO6CL2BBKRKYA/action/storage_attestation","attest_author":"https://pith.science/pith/VLR5LVSIYELJIEO6CL2BBKRKYA/action/author_attestation","sign_citation":"https://pith.science/pith/VLR5LVSIYELJIEO6CL2BBKRKYA/action/citation_signature","submit_replication":"https://pith.science/pith/VLR5LVSIYELJIEO6CL2BBKRKYA/action/replication_record"}},"created_at":"2026-07-05T10:02:50.492397+00:00","updated_at":"2026-07-05T10:02:50.492397+00:00"}