{"id":"W2479077205","doi":"10.5555/2936924.2937144","title":"Convergence and Quality of Iterative Voting under Non-Scoring Rules: (Extended Abstract)","year":2016,"lang":"en","type":"article","venue":"Adaptive Agents and Multi-Agents Systems","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Voting; Convergence (economics); Computer science; Quality (philosophy); Iterative method; Social choice theory; Anti-plurality voting; Cardinal voting systems; Mathematical optimization; Algorithm; Mathematical economics; Mathematics; Economics; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01253505,0.0003542924,0.001103846,0.001493538,0.000732295,0.002726555,0.001500888,0.001265564,0.005713043],"category_scores_gemma":[0.1224507,0.000308247,0.0009325086,0.001650483,0.003044289,0.003243884,0.001411376,0.001900659,0.0006599894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001671546,"about_ca_system_score_gemma":0.0009793441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003043516,"about_ca_topic_score_gemma":0.001424565,"domain_scores_codex":[0.9946267,0.002850436,0.0003361564,0.0007874183,0.0008688605,0.0005304803],"domain_scores_gemma":[0.8138257,0.1410255,0.01805526,0.0117087,0.01283825,0.002546532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001432711,0.0005791562,0.05590606,0.0004470328,0.0004660948,0.0003189431,0.002062413,0.426354,0.003240058,0.4234346,0.003965718,0.08179332],"study_design_scores_gemma":[0.000118059,0.0002521627,0.0132393,0.00007566503,0.00005995862,0.000166483,0.0002772785,0.6080292,0.001511368,0.3752971,0.0009226532,0.00005073775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7743272,0.000654972,0.2058285,0.0007697625,0.00005605947,0.0001719683,0.0002947935,0.0001734285,0.01772344],"genre_scores_gemma":[0.986466,0.0001302065,0.01160274,0.00004411563,0.00002452912,0.00006126134,0.0001439893,0.00003630929,0.001490811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01253505,"threshold_uncertainty_score":0.06629246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1481050922965997,"score_gpt":0.3044544472939487,"score_spread":0.1563493549973489,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}