{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0008888184,0.0001343945,0.0002827454,0.0001341003,0.0003201366,0.00004120559,0.0001435001,0.00003708196,0.003970709],"category_scores_gemma":[0.00003256449,0.0001840468,0.00007584337,0.00009149162,0.00002826537,0.000120123,0.0001504022,0.0001638004,0.000188161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003795741,"about_ca_system_score_gemma":0.00003895426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004099388,"about_ca_topic_score_gemma":0.00004175754,"domain_scores_codex":[0.9987381,0.00003685419,0.0004766857,0.0004516659,0.00002207741,0.0002746632],"domain_scores_gemma":[0.9993733,0.00003960008,0.00028704,0.0002012941,0.000007783888,0.00009096282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001379813,0.0002301239,0.0541507,0.00002156679,0.0002188599,0.00001507228,0.003990996,0.0009213645,0.000111917,0.9322075,0.0006187921,0.007375151],"study_design_scores_gemma":[0.001550763,0.0004393657,0.007227907,0.000002509626,0.00001309837,0.000105521,0.0009872344,0.004898736,0.00004336502,0.1360447,0.848123,0.0005638676],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8783382,0.0003088859,0.00008241124,0.0004556646,0.0005343411,0.0004037138,0.0003181926,0.00004736244,0.1195112],"genre_scores_gemma":[0.9958746,0.0001223207,0.000213578,0.0006224993,0.00007620903,0.000237557,0.0000392464,0.00002536051,0.002788601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8475041,"threshold_uncertainty_score":0.9969398,"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."}}