{"id":"W2261933449","doi":"10.1177/0019793915591990","title":"Returns to Apprenticeship Based on the 2006 Canadian Census","year":2015,"lang":"en","type":"article","venue":"Industrial and Labor Relations Review","topic":"Education Systems and Policy","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Imperial Bank of Commerce (Canada)","funders":"","keywords":"Apprenticeship; Certification; Census; Certificate; Instrumental variable; Quantile; Demographic economics; Econometrics; Actuarial science; Business; Economics; Geography; Demography; Computer science; Sociology; Population; Management","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":[0.001410446,0.00006062158,0.0001087752,0.00006121671,0.0003788115,0.0000750169,0.0001180142,0.00008773924,0.0007337485],"category_scores_gemma":[0.00220137,0.00004057499,0.0000260292,0.0007289912,0.00004609304,0.00004850037,0.000005700233,0.0001533022,0.0002887593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001043221,"about_ca_system_score_gemma":0.001205661,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1080774,"about_ca_topic_score_gemma":0.1051282,"domain_scores_codex":[0.9989348,0.0004320899,0.0001772996,0.0001032824,0.000188191,0.0001643061],"domain_scores_gemma":[0.9989974,0.000210983,0.00006271161,0.0001596617,0.0001359889,0.0004332644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001887958,0.000009780704,0.005384781,0.00001171662,0.000004639781,3.955787e-7,0.002802794,0.00001007224,4.286369e-8,0.1236148,0.8640013,0.004157727],"study_design_scores_gemma":[0.00008027918,0.00001163994,0.0003925633,0.0004034997,0.00001714894,1.853931e-7,0.001277163,0.000004607944,1.119951e-7,0.0001348299,0.9976211,0.00005682804],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.01295513,0.01271612,0.000001813028,0.636306,0.001374463,0.001863121,0.0002597922,0.0000386541,0.3344849],"genre_scores_gemma":[0.9382572,0.001235933,0.00006302628,0.02451776,0.003035469,0.0002032151,0.0000575191,0.00001691479,0.03261293],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9253021,"threshold_uncertainty_score":0.9112009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2135683853908326,"score_gpt":0.3818090304310367,"score_spread":0.1682406450402041,"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."}}