{"id":"W2199513138","doi":"","title":"Who gets caught? Statistical discrimination in law enforcement","year":2002,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Carleton University; Bishop's University","funders":"","keywords":"Conviction; Juvenile delinquency; Law enforcement; Enforcement; Criminology; Race (biology); Statistical discrimination; Test (biology); Psychology; Political science; Law; Economics; Demographic economics; Sociology","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.00541266,0.0001698054,0.0007296128,0.001083701,0.001256249,0.00233851,0.0007825542,0.001735801,0.009132707],"category_scores_gemma":[0.03625606,0.000307729,0.0003996415,0.001223148,0.002187047,0.001769234,0.001240726,0.00143923,0.0006523264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001044399,"about_ca_system_score_gemma":0.001030894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01052652,"about_ca_topic_score_gemma":0.007271264,"domain_scores_codex":[0.996335,0.001745871,0.0001553362,0.0004632334,0.0005462925,0.0007542529],"domain_scores_gemma":[0.9761322,0.01199939,0.008852272,0.00104191,0.0006085305,0.001365572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003529831,0.0008241927,0.8886822,0.00006782344,0.0001642656,0.0009969518,0.002207223,0.004033809,0.0002894003,0.04262542,0.004769243,0.05498645],"study_design_scores_gemma":[0.0001763878,0.0006323246,0.8197637,0.0002075164,0.0001961885,0.001561919,0.008560619,0.0359116,0.0005109535,0.1237074,0.008694373,0.00007712202],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9715031,0.001081338,0.001540653,0.01141652,0.00006727992,0.00003675647,0.0001125039,0.00001598697,0.01422589],"genre_scores_gemma":[0.9984658,0.0001605616,0.00006105395,0.0003304004,0.0000453052,0.000006664265,0.00001334747,0.000002477666,0.0009143986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01052652,"threshold_uncertainty_score":0.03055197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0946231917773193,"score_gpt":0.419017251357282,"score_spread":0.3243940595799626,"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."}}