{"id":"W2571847123","doi":"10.1017/s1743923x16000684","title":"Votes for Women: Electoral Systems and Support for Female Candidates","year":2017,"lang":"en","type":"article","venue":"Politics & Gender","topic":"Gender Politics and Representation","field":"Social Sciences","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Western University","funders":"Agence Nationale de la Recherche","keywords":"Electoral system; Parliament; Legislature; Voting; Proportional representation; Representation (politics); Affect (linguistics); Political science; Social psychology; Demographic economics; Psychology; Economics; Law; Politics; Communication; Democracy","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":[0.001440392,0.000117432,0.0001908399,0.0007243489,0.0005855433,0.001185084,0.0002366517,0.0004713197,0.0104329],"category_scores_gemma":[0.008091032,0.00008920776,0.000194859,0.0005753916,0.000564675,0.000509617,0.0007579564,0.0003339202,0.0009396963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002893136,"about_ca_system_score_gemma":0.0001561916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001396499,"about_ca_topic_score_gemma":0.003046447,"domain_scores_codex":[0.9988711,0.0006112987,0.00005649377,0.0001280171,0.0001406025,0.0001924744],"domain_scores_gemma":[0.9954716,0.001760856,0.001772711,0.0002351341,0.0002412606,0.0005185014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001517071,0.0002717871,0.9514231,0.0000508371,0.00007700531,0.000122634,0.004083742,0.000227584,0.002822366,0.002848667,0.001177612,0.03537764],"study_design_scores_gemma":[0.00002909616,0.0002388023,0.9904037,0.00001813113,0.00002178376,0.0001185921,0.004643013,0.000308389,0.000526864,0.0007334055,0.002947572,0.00001067608],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923583,0.00007951601,0.00009525919,0.0002185161,0.000008487987,0.000006254007,0.00007423345,0.000002365807,0.007157039],"genre_scores_gemma":[0.9989092,0.00001791591,0.00003655853,0.00002166015,0.000008761713,0.000003815478,0.00004436967,0.000001295416,0.000956322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0104329,"threshold_uncertainty_score":0.0349015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09256334293386646,"score_gpt":0.3913990247997294,"score_spread":0.2988356818658629,"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."}}