{"id":"W4221028357","doi":"10.1149/2.f08221if","title":"Diversity, Equality, and Inclusion in Our Professions: A Thin and Leaky Pipeline","year":2022,"lang":"en","type":"article","venue":"The Electrochemical Society Interface","topic":"Career Development and Diversity","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Lagging; Inclusion (mineral); Diversity (politics); Politics; Enlightenment; Political science; Sociology; Public relations; Social science; Law; Epistemology; Mathematics; Philosophy","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.001541467,0.00008270924,0.0001141762,0.00001479764,0.006809202,0.00002369218,0.0004282052,0.00006183442,0.00004977372],"category_scores_gemma":[0.00007956524,0.00006971631,0.00004696123,0.0002546989,0.0001342651,0.0000875389,0.03541237,0.0004716588,0.000001247665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002992244,"about_ca_system_score_gemma":0.000064839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001573305,"about_ca_topic_score_gemma":0.0004517744,"domain_scores_codex":[0.9987285,0.0002142061,0.0001049568,0.0001978766,0.0004848264,0.0002696264],"domain_scores_gemma":[0.9996738,0.0001121838,0.00004520819,0.00007482206,0.00002837381,0.00006554289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001922006,0.0001696291,0.03043509,0.00002637022,0.00003712178,0.000002068027,0.9144319,0.000002888386,0.02975162,0.002311003,0.02121696,0.001423166],"study_design_scores_gemma":[0.003810168,0.0002536169,0.005147236,0.0001037213,0.0001175344,0.00001484679,0.8222907,0.001932523,0.02436114,0.09301272,0.04770109,0.001254663],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9701282,0.000660074,0.0003417276,0.02727108,0.0000722516,0.000237456,0.000003309051,0.00004735362,0.001238531],"genre_scores_gemma":[0.9968192,0.0001904117,0.0001009365,0.0009837314,0.00003742215,0.000006482868,0.000003153009,0.000003493929,0.001855152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09214113,"threshold_uncertainty_score":0.9944838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02683401721854276,"score_gpt":0.3078331665046565,"score_spread":0.2809991492861137,"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."}}