{"id":"W2796369625","doi":"10.1111/josi.12256","title":"Benefiting from Diversity: How Groups’ Coordinating Mechanisms Affect Leadership Opportunities for Marginalized Individuals","year":2018,"lang":"en","type":"article","venue":"Journal of Social Issues","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Science Foundation","keywords":"Diversity (politics); Moderation; Prosperity; Affect (linguistics); Social psychology; Set (abstract data type); Inclusion (mineral); Mechanism (biology); Psychology; Public relations; Sociology; Political science; Epistemology","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":[0.001685357,0.0001393827,0.0001964893,0.0004353084,0.001634869,0.001774652,0.0003131757,0.0004264279,0.003703627],"category_scores_gemma":[0.009367667,0.00009502928,0.0001565271,0.000224371,0.001439432,0.0007451632,0.001862236,0.000509074,0.0001940839],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005706988,"about_ca_system_score_gemma":0.0005844117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002875888,"about_ca_topic_score_gemma":0.004518679,"domain_scores_codex":[0.9985361,0.0007770375,0.00003565588,0.0001315107,0.000143889,0.0003756641],"domain_scores_gemma":[0.9947291,0.002090574,0.001141284,0.0002699099,0.0003016075,0.001467528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006205969,0.0005130734,0.9182563,0.00004172847,0.0001010663,0.0003392395,0.03918315,0.000474407,0.003007253,0.005079853,0.0006762743,0.03170707],"study_design_scores_gemma":[0.0000276481,0.0003446341,0.9442545,0.00004725621,0.00003434856,0.0001477949,0.04596237,0.000955215,0.0005330275,0.006384412,0.001290669,0.00001813862],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983234,0.00003664789,0.0001028012,0.0001955327,0.00000344153,0.000002378717,0.000005126614,0.000001062457,0.001329613],"genre_scores_gemma":[0.9998611,0.000006617712,0.0000287238,0.00001259633,0.000001933477,0.000001570527,0.000002231688,4.777301e-7,0.0000846899],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003703627,"threshold_uncertainty_score":0.01238984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4498836505634218,"score_gpt":0.360164380486786,"score_spread":0.08971927007663577,"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."}}