{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:RLV6OQX7GGCUP7TTG3YNJ6V5RP","short_pith_number":"pith:RLV6OQX7","schema_version":"1.0","canonical_sha256":"8aebe742ff318547fe7336f0d4fabd8bd6c67b00bec709ea7ae2dce66f693a6c","source":{"kind":"arxiv","id":"2403.18340","version":2},"attestation_state":"computed","paper":{"title":"The Metric Distortion of Randomized Social Choice Functions: C1 Maximal Lottery Rules and Simulations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Fabian Frank, Patrick Lederer","submitted_at":"2024-03-27T08:31:09Z","abstract_excerpt":"The metric distortion of a randomized social choice function (RSCF) quantifies its worst-case approximation ratio to the optimal social cost when the voters' costs for alternatives are given by distances in a metric space. This notion has recently attracted significant attention as numerous RSCFs that aim to minimize the metric distortion have been suggested. Since such tailored voting rules have, however, little normative appeal other than their low metric distortion, we will study the metric distortion of well-established RSCFs. Specifically, we first show that C1 maximal lottery rules, a we"},"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":"2403.18340","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GT","submitted_at":"2024-03-27T08:31:09Z","cross_cats_sorted":[],"title_canon_sha256":"23abf06e4fd863d6beacc92b700fdb39e52414e6b1571dac28bd63b31b706523","abstract_canon_sha256":"6faf627af2ba2eb5f21187a69545a6857c9023033a12c256ffbc9ab26bed3098"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:12:59.436453Z","signature_b64":"Rdxd6MvPRt/k+7so4xNDSJ19uoYqAVupRSJUWZHXq4qSABLZ/gqHEYyPoRfwgSRJgkCMDh/w0SDk3R9/AFyfDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8aebe742ff318547fe7336f0d4fabd8bd6c67b00bec709ea7ae2dce66f693a6c","last_reissued_at":"2026-07-05T10:12:59.435970Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:12:59.435970Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Metric Distortion of Randomized Social Choice Functions: C1 Maximal Lottery Rules and Simulations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.GT","authors_text":"Fabian Frank, Patrick Lederer","submitted_at":"2024-03-27T08:31:09Z","abstract_excerpt":"The metric distortion of a randomized social choice function (RSCF) quantifies its worst-case approximation ratio to the optimal social cost when the voters' costs for alternatives are given by distances in a metric space. This notion has recently attracted significant attention as numerous RSCFs that aim to minimize the metric distortion have been suggested. Since such tailored voting rules have, however, little normative appeal other than their low metric distortion, we will study the metric distortion of well-established RSCFs. Specifically, we first show that C1 maximal lottery rules, a we"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.18340","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/2403.18340/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":"2403.18340","created_at":"2026-07-05T10:12:59.436027+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.18340v2","created_at":"2026-07-05T10:12:59.436027+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.18340","created_at":"2026-07-05T10:12:59.436027+00:00"},{"alias_kind":"pith_short_12","alias_value":"RLV6OQX7GGCU","created_at":"2026-07-05T10:12:59.436027+00:00"},{"alias_kind":"pith_short_16","alias_value":"RLV6OQX7GGCUP7TT","created_at":"2026-07-05T10:12:59.436027+00:00"},{"alias_kind":"pith_short_8","alias_value":"RLV6OQX7","created_at":"2026-07-05T10:12:59.436027+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.13630","citing_title":"Metric Distortion for Tournament Voting and Beyond","ref_index":1984,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RLV6OQX7GGCUP7TTG3YNJ6V5RP","json":"https://pith.science/pith/RLV6OQX7GGCUP7TTG3YNJ6V5RP.json","graph_json":"https://pith.science/api/pith-number/RLV6OQX7GGCUP7TTG3YNJ6V5RP/graph.json","events_json":"https://pith.science/api/pith-number/RLV6OQX7GGCUP7TTG3YNJ6V5RP/events.json","paper":"https://pith.science/paper/RLV6OQX7"},"agent_actions":{"view_html":"https://pith.science/pith/RLV6OQX7GGCUP7TTG3YNJ6V5RP","download_json":"https://pith.science/pith/RLV6OQX7GGCUP7TTG3YNJ6V5RP.json","view_paper":"https://pith.science/paper/RLV6OQX7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.18340&json=true","fetch_graph":"https://pith.science/api/pith-number/RLV6OQX7GGCUP7TTG3YNJ6V5RP/graph.json","fetch_events":"https://pith.science/api/pith-number/RLV6OQX7GGCUP7TTG3YNJ6V5RP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RLV6OQX7GGCUP7TTG3YNJ6V5RP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RLV6OQX7GGCUP7TTG3YNJ6V5RP/action/storage_attestation","attest_author":"https://pith.science/pith/RLV6OQX7GGCUP7TTG3YNJ6V5RP/action/author_attestation","sign_citation":"https://pith.science/pith/RLV6OQX7GGCUP7TTG3YNJ6V5RP/action/citation_signature","submit_replication":"https://pith.science/pith/RLV6OQX7GGCUP7TTG3YNJ6V5RP/action/replication_record"}},"created_at":"2026-07-05T10:12:59.436027+00:00","updated_at":"2026-07-05T10:12:59.436027+00:00"}