{"id":"W282489851","doi":"","title":"Gender Inequity in Business Academia: Past and Present","year":2010,"lang":"en","type":"article","venue":"Forum on public policy","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Salary; Political science; Higher education; Public relations; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003527241,0.0006091137,0.0007880597,0.004141613,0.003939613,0.00789402,0.0007046578,0.003027931,0.006217202],"category_scores_gemma":[0.004590354,0.000567716,0.0003698984,0.01110551,0.007523,0.00941082,0.003715679,0.004437115,0.0005191017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004422878,"about_ca_system_score_gemma":0.004279633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01623343,"about_ca_topic_score_gemma":0.01799399,"domain_scores_codex":[0.9982969,0.0005342241,0.000102868,0.0004248889,0.0003731745,0.0002679357],"domain_scores_gemma":[0.9940937,0.003548204,0.0007363402,0.0001378335,0.0007729662,0.0007108431],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001270748,0.0002736977,0.04929686,0.004661825,0.00005458017,0.0003380209,0.05483609,0.0002876735,0.0002808099,0.1264943,0.09478762,0.6685614],"study_design_scores_gemma":[0.00001181774,0.0002518705,0.173482,0.0195993,0.00006048885,0.00121953,0.08349433,0.0002991762,0.0001981088,0.03501924,0.6862469,0.0001171887],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02348067,0.8487168,0.0003231682,0.09969664,0.003683166,0.00001413055,0.0004082092,0.00001514582,0.02366213],"genre_scores_gemma":[0.2879615,0.6786264,0.0003976127,0.01319081,0.01486692,0.00005700921,0.0003702886,0.00002324696,0.004506324],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9964728,"threshold_uncertainty_score":0.03227788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1147032212537684,"score_gpt":0.3476872592652488,"score_spread":0.2329840380114804,"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."}}