{"id":"W2154776903","doi":"10.1007/s00181-006-0092-3","title":"The impact of unionization on the incidence of and sources of payment for training in Canada","year":2006,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Seniority; Payment; Nonunion; Training (meteorology); Variety (cybernetics); Human capital; Labour economics; Business; Control (management); Demographic economics; Capital (architecture); Incidence (geometry); Economics; Economic growth; Finance; Political science; Medicine; Management; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007488795,0.00006445271,0.000238644,0.00003693469,0.00003713511,0.00001046099,0.0001242258,0.00002824575,0.000006733484],"category_scores_gemma":[0.0001602842,0.0000445626,0.00005287726,0.00008492761,0.00006210717,0.00003389249,0.00002425064,0.00004501994,9.543079e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002018262,"about_ca_system_score_gemma":0.0002167161,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3532419,"about_ca_topic_score_gemma":0.3021832,"domain_scores_codex":[0.9991334,0.00001794425,0.0006076519,0.0001147523,0.0000146948,0.0001115256],"domain_scores_gemma":[0.9986778,0.0006739254,0.0004585856,0.0001481644,0.00002484245,0.00001663715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003553927,0.00002229376,0.6425208,0.00001168153,0.00001881563,6.923558e-8,0.0002344631,0.01939828,0.000002255094,0.3366615,0.00004155609,0.001052753],"study_design_scores_gemma":[0.0003222789,0.00009529794,0.690774,0.00001283398,0.000002293198,3.199877e-7,0.00026177,0.07949731,0.00008736692,0.2284526,0.0004033781,0.00009056567],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997876,0.0001410558,0.0002104954,0.0007060439,0.00003961341,0.000142309,0.0002405108,8.309251e-7,0.0006431255],"genre_scores_gemma":[0.9997534,0.0001085112,0.00004490552,0.00004786427,0.00001466604,0.000006613512,0.000004944251,0.000005856959,0.00001328044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1082089,"threshold_uncertainty_score":0.7105501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03833936198786177,"score_gpt":0.2581730195573841,"score_spread":0.2198336575695224,"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."}}