{"id":"W2510333687","doi":"10.5509/2016892325","title":"Reserved for Whom? The Electoral Impact of Gender Quotas in Taiwan","year":2016,"lang":"en","type":"article","venue":"Pacific Affairs","topic":"Gender Politics and Representation","field":"Social Sciences","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Political science; Demographic economics; Gender studies; Economics; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000598269,0.00006061234,0.00009638402,0.00005214332,0.0001659494,0.00002949562,0.000162931,0.00005493642,0.0001029906],"category_scores_gemma":[0.0002018065,0.00003113498,0.0001126473,0.0001594652,0.0002434573,0.00008095908,0.00001628843,0.00003731722,0.000008149436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001115426,"about_ca_system_score_gemma":0.0002567695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001828619,"about_ca_topic_score_gemma":0.001970071,"domain_scores_codex":[0.9990675,0.0001475336,0.0001539184,0.0001283246,0.0001950982,0.0003075636],"domain_scores_gemma":[0.9994844,0.0001440308,0.00006875055,0.0001623815,0.00008186303,0.00005853001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002209289,0.0002854356,0.5167818,0.00005502084,0.0001976686,0.00000354712,0.2296469,0.00008368785,0.02048579,0.1998914,0.02494021,0.007407664],"study_design_scores_gemma":[0.001600517,0.0002104174,0.144146,0.00003392371,0.00002654561,9.250001e-7,0.7695673,0.0001420482,0.001713009,0.07716981,0.005077386,0.0003120767],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5048515,0.0002738642,0.001494807,0.006466926,0.0005971537,0.001345613,0.0001121789,0.00005604975,0.4848019],"genre_scores_gemma":[0.9983696,0.0000110018,0.00005388143,0.000001878981,0.0001152011,0.00002367276,0.000002587211,0.0000072428,0.001414964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5399204,"threshold_uncertainty_score":0.2764337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0607025332321172,"score_gpt":0.3537108752071447,"score_spread":0.2930083419750275,"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."}}