{"id":"W4411689376","doi":"10.2139/ssrn.5320509","title":"Trickle-down & Bottom-up Effects on Workplace Gender Diversity","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Diversity (politics); 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":[0.001473652,0.0003373657,0.0005752951,0.0005125241,0.00167873,0.002007273,0.0005509662,0.001253428,0.0733826],"category_scores_gemma":[0.008695303,0.0002355503,0.0005719196,0.0008775698,0.001356981,0.002237125,0.003824246,0.00252086,0.003566921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008130551,"about_ca_system_score_gemma":0.0008442436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006283456,"about_ca_topic_score_gemma":0.01041662,"domain_scores_codex":[0.9989069,0.0005265246,0.00002669517,0.0001476294,0.0001465029,0.000245819],"domain_scores_gemma":[0.988756,0.007444274,0.0008791468,0.0009157469,0.000394025,0.001610691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.008786805,0.004375276,0.3302489,0.001742906,0.0008731845,0.001268898,0.03937563,0.003140439,0.01123741,0.1580995,0.08629128,0.3545597],"study_design_scores_gemma":[0.0003145162,0.001178263,0.8517106,0.0003898403,0.0003809305,0.0001170687,0.02189309,0.001785585,0.003059676,0.08490655,0.03414907,0.0001146626],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9026293,0.001042049,0.00316075,0.008539351,0.0002862136,0.00005752922,0.001863593,0.0001465499,0.08227457],"genre_scores_gemma":[0.9885767,0.0002153604,0.0004609005,0.0006592188,0.00005682453,0.00003023961,0.0001407701,0.00003773717,0.009822196],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0733826,"threshold_uncertainty_score":0.2454892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06800599646896782,"score_gpt":0.3126421962533538,"score_spread":0.244636199784386,"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."}}