{"id":"W2905179838","doi":"","title":"Race and Retention in a Competitive Labor Market","year":2018,"lang":"en","type":"article","venue":"Journal of Sports Economics","topic":"Sports, Gender, and Society","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Basketball; Race (biology); Quarter (Canadian coin); Sample (material); Demographic economics; Labour economics; White (mutation); Economics; Advertising; Psychology; Marketing; Business; Sociology; Gender studies; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001554038,0.00005432891,0.0001793206,0.00006257701,0.0001116327,0.00004032016,0.00007534986,0.00007442595,0.0004593459],"category_scores_gemma":[0.00004116834,0.00005550617,0.0000588171,0.00006905195,0.0002281329,0.0002337306,0.00001388226,0.0001062873,0.000001270523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001436365,"about_ca_system_score_gemma":0.0002159852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001598656,"about_ca_topic_score_gemma":0.001135304,"domain_scores_codex":[0.9993386,0.00002738355,0.0003198077,0.00008913225,0.00008353621,0.000141591],"domain_scores_gemma":[0.9993554,0.00002944156,0.000353445,0.00005363408,0.0001175191,0.00009059668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001648238,0.00008048455,0.8340787,0.00001149546,0.0000454002,0.00006058111,0.1038988,0.000006736727,0.00001430434,0.04524591,0.007725553,0.008667228],"study_design_scores_gemma":[0.0006093456,0.00006947009,0.7373075,0.00005950403,0.00001838626,0.00002542022,0.1039993,0.00005268606,0.00001805232,0.00538611,0.1523197,0.0001345299],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9523817,0.0001580603,0.000007844736,0.0009355639,0.0005548666,0.00005706814,0.00000241111,0.000003813341,0.04589867],"genre_scores_gemma":[0.9907691,0.004795178,0.0005524247,0.0002862504,0.0006540251,3.847652e-7,4.414728e-7,0.000005949377,0.002936268],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1445941,"threshold_uncertainty_score":0.5029515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01651041112994761,"score_gpt":0.2634434602598325,"score_spread":0.2469330491298848,"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."}}