{"id":"W3161542587","doi":"10.1016/j.electstud.2021.102340","title":"Electoral incentives and elite racial identification: Why Brazilian politicians change their race","year":2021,"lang":"en","type":"article","venue":"Electoral Studies","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Elite; Race (biology); Extant taxon; Political science; Incentive; Competition (biology); Political economy; Politics; Identification (biology); Quarter (Canadian coin); Position (finance); Sociology; Gender studies; Economics; Geography; Law; Market economy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004032625,0.0001521092,0.0002961058,0.001244483,0.003664084,0.00266959,0.0005461749,0.0009037529,0.01136408],"category_scores_gemma":[0.0185244,0.0001714876,0.0002273954,0.001701096,0.002359529,0.001422213,0.001748871,0.0009597141,0.0005441057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002583242,"about_ca_system_score_gemma":0.002944905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05549956,"about_ca_topic_score_gemma":0.1352265,"domain_scores_codex":[0.9975991,0.0009468421,0.00005358065,0.0002186083,0.0002768258,0.0009049749],"domain_scores_gemma":[0.9942781,0.00241758,0.00103463,0.0003999568,0.0008780411,0.0009916349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003590373,0.000367842,0.5836531,0.0002413883,0.00009087247,0.0003850251,0.08060771,0.0002897078,0.001575919,0.2200248,0.008944184,0.1034604],"study_design_scores_gemma":[0.00003507295,0.00006117758,0.8301471,0.0002956887,0.00007273573,0.0001276633,0.08716422,0.0005573468,0.0003678779,0.01776145,0.06338738,0.0000222355],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9162394,0.0007431457,0.0003794112,0.009905563,0.00006231808,0.00002130441,0.0001351497,0.000006279891,0.07250727],"genre_scores_gemma":[0.9972169,0.0001446191,0.00006384963,0.0002500234,0.00001719557,0.000007004165,0.00002113847,0.000003903041,0.00227531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05549956,"threshold_uncertainty_score":0.110353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.110760537061196,"score_gpt":0.3992520931591698,"score_spread":0.2884915560979737,"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."}}