{"id":"W2029570589","doi":"10.1111/irel.12092","title":"Do Train‐or‐Pay Schemes Really Increase Training Levels?","year":2015,"lang":"en","type":"article","venue":"Industrial Relations A Journal of Economy and Society","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Incentive; Portfolio; Training (meteorology); Human capital; Identification (biology); Business; Order (exchange); Economics; Public economics; Labour economics; Finance; Microeconomics; Economic growth","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":[0.001932749,0.0001256163,0.0002555421,0.0004551206,0.0006672003,0.001489497,0.0007017248,0.001089774,0.008834911],"category_scores_gemma":[0.01620446,0.0001103691,0.0002541244,0.0007924111,0.001367185,0.001027747,0.0009010432,0.001021848,0.0004774232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003365027,"about_ca_system_score_gemma":0.003834441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05495913,"about_ca_topic_score_gemma":0.1110717,"domain_scores_codex":[0.9980487,0.0005816441,0.00005050788,0.0001469499,0.0004746832,0.0006974512],"domain_scores_gemma":[0.9913328,0.003444362,0.002842719,0.000357956,0.0007309918,0.001291015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001435776,0.002392426,0.6318944,0.0007518332,0.000346249,0.0002210228,0.001902373,0.007236445,0.005144855,0.07241026,0.01865589,0.2576084],"study_design_scores_gemma":[0.000132657,0.000622821,0.962354,0.0001999421,0.00008508251,0.00002999182,0.002029773,0.002072029,0.001615069,0.007212978,0.02362552,0.00002014535],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9061605,0.00134354,0.002392391,0.033244,0.000242942,0.0001571962,0.001048092,0.00008314435,0.05532817],"genre_scores_gemma":[0.9962835,0.000177099,0.000367485,0.001034713,0.00004460322,0.00002379147,0.00007415959,0.000005452665,0.001989118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05495913,"threshold_uncertainty_score":0.1092784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1949052967989795,"score_gpt":0.2868259206183081,"score_spread":0.09192062381932861,"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."}}