{"id":"W3165696130","doi":"10.1017/psrm.2024.10","title":"The best at the top? Candidate ranking strategies under closed list proportional representation","year":2024,"lang":"en","type":"article","venue":"Political Science Research and Methods","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"CONTEST; Proportional representation; Incentive; Legislature; Competence (human resources); Rank (graph theory); Ranking (information retrieval); Order (exchange); Political science; Public relations; Microeconomics; Computer science; Politics; Economics; Law; Mathematics; Information retrieval; Management","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":[0.006686061,0.0005642172,0.001099261,0.001332018,0.001896407,0.004339317,0.001291552,0.001980806,0.0183887],"category_scores_gemma":[0.02249566,0.0003672568,0.0004876551,0.001146441,0.001596393,0.003295649,0.0027495,0.001643888,0.001832503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001771729,"about_ca_system_score_gemma":0.001073969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00189284,"about_ca_topic_score_gemma":0.001974164,"domain_scores_codex":[0.9929011,0.004656796,0.0001594177,0.0004972387,0.0006357321,0.001149709],"domain_scores_gemma":[0.9884884,0.00759492,0.001384696,0.0008104701,0.000612326,0.001109274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002608893,0.001586072,0.01240085,0.0004621969,0.0002088771,0.0006818965,0.003556639,0.0729511,0.00778962,0.6995068,0.01148996,0.1867572],"study_design_scores_gemma":[0.0007473994,0.002175888,0.01171411,0.0001638787,0.0001664923,0.0004682127,0.004757697,0.490155,0.003804648,0.4647539,0.02093086,0.0001619356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7795928,0.0002849547,0.09472435,0.004161284,0.0001035491,0.0003523105,0.0002144631,0.0001998452,0.1203665],"genre_scores_gemma":[0.9880449,0.00004367695,0.00526956,0.0001516885,0.00002777576,0.00006258189,0.00003363564,0.00001490536,0.006351212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0183887,"threshold_uncertainty_score":0.06151628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2597051134036285,"score_gpt":0.6149408002078486,"score_spread":0.3552356868042201,"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."}}