{"id":"W4393261445","doi":"10.1111/ijsa.12467","title":"How does bias enter the employment interview? Identifying the riskiest applicant characteristics, interviewer characteristics, and sources of potentially biasing information","year":2024,"lang":"en","type":"article","venue":"International Journal of Selection and Assessment","topic":"Employer Branding and e-HRM","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Interview; Psychology; Applied psychology; Social psychology; Political science; Law","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.2595718,0.0004542958,0.001054919,0.003812788,0.003175108,0.004502941,0.001034448,0.001521372,0.001557489],"category_scores_gemma":[0.4119386,0.0008195954,0.0008490551,0.002878579,0.005860722,0.005192165,0.004218832,0.001767945,0.0003415745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002410029,"about_ca_system_score_gemma":0.003967027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003131727,"about_ca_topic_score_gemma":0.005162857,"domain_scores_codex":[0.6993989,0.2434956,0.01748398,0.004864724,0.03093905,0.003817752],"domain_scores_gemma":[0.4171853,0.483582,0.06521796,0.01471716,0.01734311,0.001954429],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006318981,0.0001631567,0.7016399,0.001533396,0.0005211437,0.0005868839,0.1106764,0.0006290637,0.00199191,0.01125832,0.0019422,0.1684258],"study_design_scores_gemma":[0.0001599451,0.001088921,0.6222397,0.007919325,0.0009569547,0.003686598,0.2194397,0.008579998,0.01075616,0.08600248,0.03865752,0.0005127953],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9072457,0.004248814,0.05872611,0.01802429,0.0003692763,0.0006933201,0.0002725933,0.00006665956,0.0103533],"genre_scores_gemma":[0.9865646,0.0007853776,0.01021491,0.001562247,0.0001972099,0.0002111045,0.00004282946,0.00001657267,0.0004052084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2595718,"threshold_uncertainty_score":0.9130799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03264539120569861,"score_gpt":0.2845646314378773,"score_spread":0.2519192402321787,"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."}}