{"id":"W4291163689","doi":"10.1111/ecca.12441","title":"Training, Recruitment, and Outplacement as Endogenous Adverse Selection","year":2022,"lang":"en","type":"article","venue":"Economica","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Adverse selection; Human capital; Business; Human capital theory; Labour economics; Selection (genetic algorithm); Training (meteorology); Service (business); Actuarial science; Economics; Marketing; Computer science; Economic growth","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":[0.003561632,0.0005164706,0.000948058,0.0005919227,0.001286624,0.002553551,0.001137094,0.002200685,0.01138526],"category_scores_gemma":[0.008409534,0.0003976788,0.0006946672,0.0005663899,0.002963898,0.002385841,0.002107409,0.00179735,0.0008616771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0019274,"about_ca_system_score_gemma":0.001570491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004357973,"about_ca_topic_score_gemma":0.003455122,"domain_scores_codex":[0.9979169,0.001019738,0.00005824517,0.0002114771,0.0002186955,0.0005749151],"domain_scores_gemma":[0.9929978,0.003305647,0.001958398,0.0004339341,0.0002840977,0.001020177],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005948739,0.0006295543,0.02590903,0.0001378081,0.00005835536,0.001717948,0.001283018,0.1407829,0.002082402,0.791352,0.00644089,0.02901112],"study_design_scores_gemma":[0.0004334701,0.0003836463,0.014018,0.00007415112,0.00004186647,0.0005596855,0.0007672984,0.2992873,0.0005668692,0.6781688,0.00562002,0.0000788777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.752227,0.001274543,0.1558808,0.01373381,0.0002872737,0.0003411269,0.00052773,0.0001633098,0.07556427],"genre_scores_gemma":[0.9831555,0.000433592,0.001638156,0.0003383441,0.0001335224,0.0000748289,0.00003927256,0.000008767541,0.01417812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01138526,"threshold_uncertainty_score":0.03808749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1311423135503944,"score_gpt":0.259655984669166,"score_spread":0.1285136711187716,"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."}}