{"id":"W3178214539","doi":"10.7202/1083608ar","title":"Can older workers be retrained? Canadian evidence from worker-firm linked data","year":2021,"lang":"en","type":"article","venue":"Relations industrielles","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Society of Canada; University of Toronto; Memorial University of Newfoundland","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Propensity score matching; Training (meteorology); Affect (linguistics); Operations management; Business; Demographic economics; Reading (process); Psychology; Computer science; Statistics; Economics; Mathematics; Geography; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.01158572,0.0005334713,0.0009933189,0.004625971,0.003077478,0.002864045,0.004020595,0.001598122,0.01000088],"category_scores_gemma":[0.06981316,0.0006328935,0.001636595,0.0134,0.001456121,0.001694746,0.002890773,0.002183974,0.0008640445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01913556,"about_ca_system_score_gemma":0.03116475,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9840186,"about_ca_topic_score_gemma":0.9818156,"domain_scores_codex":[0.9903299,0.001465235,0.001099184,0.00162387,0.003548665,0.001933174],"domain_scores_gemma":[0.9082494,0.01872733,0.02841683,0.005891135,0.03146145,0.007253767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003297589,0.00007219896,0.9494632,0.00105059,0.0006848394,0.0002142993,0.002430194,0.0003409259,0.00002929544,0.001909061,0.01687435,0.02660119],"study_design_scores_gemma":[0.00006677981,0.0000499577,0.9773133,0.00161407,0.000431345,0.00006255054,0.002229308,0.0004051194,0.00003829926,0.0004546432,0.0172984,0.00003623111],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7170462,0.09197717,0.001579836,0.03443077,0.0007498632,0.0003909275,0.09418686,0.000109271,0.05952906],"genre_scores_gemma":[0.9607133,0.01666005,0.0006701542,0.003222082,0.0001804007,0.00008669773,0.01435122,0.00003066433,0.004085459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01913556,"threshold_uncertainty_score":0.1388388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3579743699358445,"score_gpt":0.4090894692682121,"score_spread":0.05111509933236758,"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."}}