{"id":"W2982234014","doi":"10.1111/ijsa.12270","title":"Selection of gender‐incongruent applicants: No gender bias with structured interviews","year":2019,"lang":"en","type":"article","venue":"International Journal of Selection and Assessment","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Interview; Psychology; Social psychology; Applied psychology; Semi-structured interview; Personnel selection; Gender bias; Sample (material); Qualitative research; Statistics; Sociology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007220162,0.00008257635,0.0001671301,0.0001587674,0.00009105067,0.00007133243,0.000175912,0.00005449177,0.0009667784],"category_scores_gemma":[0.00002103533,0.00006699462,0.0000678732,0.0001408402,0.00004569651,0.0003333986,0.00002918027,0.00019826,0.00000492806],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002534451,"about_ca_system_score_gemma":0.0002982486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003799653,"about_ca_topic_score_gemma":0.0003484577,"domain_scores_codex":[0.9985739,0.0001616791,0.0003210174,0.0001220379,0.0007080238,0.0001133202],"domain_scores_gemma":[0.9983526,0.00003736317,0.0004813117,0.0000367845,0.001013519,0.00007846025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007286178,0.0006842823,0.8962767,0.0001060663,0.001585092,0.000007753813,0.01254439,0.0006224356,0.01650542,0.04041558,0.002322311,0.02820143],"study_design_scores_gemma":[0.005747349,0.00180212,0.7460161,0.0002143661,0.0002280538,0.0002193563,0.032922,0.002155636,0.007807587,0.005695325,0.1965425,0.0006496629],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9749714,0.00003367598,0.007223497,0.000505575,0.001016624,0.000180954,0.000006709768,0.00001181409,0.01604975],"genre_scores_gemma":[0.9970908,0.0001956097,0.002108793,0.000150445,0.0002201079,0.000001173312,0.000002482062,0.000004240194,0.0002264152],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1942202,"threshold_uncertainty_score":0.9999465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09179084363028296,"score_gpt":0.3591855997374667,"score_spread":0.2673947561071838,"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."}}