{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.07638465,0.0003525603,0.0004873187,0.001498811,0.001378231,0.001356914,0.0008811951,0.00039481,0.002854156],"category_scores_gemma":[0.1818017,0.000320786,0.0005503438,0.0009192852,0.002032006,0.001168515,0.002710791,0.0004938818,0.0004155621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006271459,"about_ca_system_score_gemma":0.001568327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001305406,"about_ca_topic_score_gemma":0.00330906,"domain_scores_codex":[0.8886219,0.09050701,0.00451254,0.003328498,0.01100576,0.002024277],"domain_scores_gemma":[0.8406318,0.1114626,0.01958755,0.01231696,0.01441718,0.001583941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00281701,0.0006989922,0.6979964,0.0008330175,0.0002760358,0.0005507621,0.1467725,0.0007355372,0.008842366,0.003643233,0.002183049,0.134651],"study_design_scores_gemma":[0.0003687321,0.004114059,0.8140947,0.001188083,0.0003058544,0.001227787,0.1303813,0.01235801,0.0161985,0.01000325,0.009543352,0.0002163373],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811313,0.0001052538,0.01390344,0.0001848865,0.00004088286,0.00110295,0.0001019116,0.00001679451,0.003412534],"genre_scores_gemma":[0.9925534,0.00004072801,0.006191702,0.000114058,0.00002197945,0.0006640589,0.00007303645,0.000007397384,0.0003335083],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07638465,"threshold_uncertainty_score":0.4039655,"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."}}