{"id":"W4322603988","doi":"10.2139/ssrn.4368610","title":"Discrimination in the Spotlight: The Effects of Political and Religious Bias on Consumer Behavior and Labor Markets","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Culture, Economy, and Development Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Politics; Polarization (electrochemistry); Unintended consequences; Empirical evidence; Political activism; Social psychology; Economics; Demographic economics; Psychology; Political science; Law","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":[0.002288189,0.0001307971,0.0003138722,0.0005434168,0.0009837741,0.001626825,0.0004206965,0.001462666,0.01147523],"category_scores_gemma":[0.01477353,0.0001643386,0.0004340405,0.0008412696,0.001807834,0.0008428383,0.0008771177,0.001411501,0.0006091932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006086189,"about_ca_system_score_gemma":0.0007164191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01193646,"about_ca_topic_score_gemma":0.01831711,"domain_scores_codex":[0.998701,0.0008086691,0.00003335207,0.0001027469,0.0001346417,0.0002195974],"domain_scores_gemma":[0.9801711,0.01290337,0.003289723,0.0007726231,0.000574777,0.002288451],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00180431,0.001498218,0.9760092,0.00002375668,0.0001470906,0.0002545197,0.002644246,0.0002074747,0.0009569648,0.002943565,0.0006496112,0.01286097],"study_design_scores_gemma":[0.00004477891,0.0001574359,0.9938163,0.00001436083,0.00006049626,0.00006274552,0.003268194,0.0004417426,0.0001846208,0.001461889,0.0004763439,0.00001109788],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951022,0.0002243166,0.00003725609,0.00108098,0.00001346038,0.000003904425,0.00003888137,0.000001187913,0.003497892],"genre_scores_gemma":[0.9992699,0.0000580757,0.00001516368,0.0001293746,0.0000174225,0.000001369426,0.00001961803,0.000002160162,0.0004870121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01193646,"threshold_uncertainty_score":0.03838849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01854492429710813,"score_gpt":0.2970356766691934,"score_spread":0.2784907523720853,"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."}}