{"id":"W2982353178","doi":"10.1177/0170840619875480","title":"Not just good for her: A temporal analysis of the dynamic relationship between representation of women and collective employee turnover","year":2019,"lang":"en","type":"article","venue":"Organization Studies","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Representation (politics); Workforce; Spillover effect; Turnover; Demographic economics; Psychology; Population; Social psychology; Sociology; Political science; Economics; Demography; Management; Microeconomics; Economic growth","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":[0.002120334,0.00009804516,0.000209572,0.001155999,0.0007058891,0.001104194,0.0003721269,0.000419061,0.004524925],"category_scores_gemma":[0.008325433,0.00009168789,0.0003685312,0.001224819,0.0003307936,0.0008970384,0.0008864175,0.0007671615,0.0003449058],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005482984,"about_ca_system_score_gemma":0.0006900981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01715492,"about_ca_topic_score_gemma":0.02088694,"domain_scores_codex":[0.9995279,0.000205687,0.00001979828,0.00007372355,0.00006203907,0.0001108031],"domain_scores_gemma":[0.9958364,0.002052865,0.0009888808,0.0002714362,0.0003753405,0.0004751004],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001766117,0.0001131417,0.9756905,0.00002184463,0.00005429628,0.0001986845,0.00609424,0.0004843969,0.0003493135,0.003027411,0.0008859403,0.01290364],"study_design_scores_gemma":[0.000004888067,0.00008613629,0.979381,0.00003037958,0.00003738666,0.0001283062,0.01130317,0.005983354,0.00009605716,0.00147531,0.001461146,0.00001279217],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968934,0.0001181133,0.0009837871,0.0004414531,0.000007592398,0.000007601744,0.0001896551,0.000005007951,0.001353371],"genre_scores_gemma":[0.999146,0.00004088639,0.0002190666,0.0000221307,0.000006281292,0.000008629623,0.0001356201,0.000002533367,0.000418828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01715492,"threshold_uncertainty_score":0.03411013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1356328660167557,"score_gpt":0.3561795739259256,"score_spread":0.2205467079091699,"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."}}