{"id":"W2616511777","doi":"10.1086/703255","title":"Push and Pull: Disability Insurance, Regional Labor Markets, and Benefit Generosity in Canada and the United States","year":2019,"lang":"en","type":"article","venue":"Journal of Labor Economics","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; University of British Columbia","funders":"","keywords":"Generosity; Disability insurance; Labour economics; Economics; Demographic economics; Health insurance; Disability benefits; Instrumental variable; Economic growth; Social security; Political science; Health care; Market economy","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":[0.001954829,0.000264527,0.0006452291,0.001669462,0.002801865,0.002694605,0.001142148,0.0007970041,0.004150504],"category_scores_gemma":[0.006840197,0.0001882474,0.0008297371,0.002944513,0.00186284,0.0009143318,0.002292351,0.001473035,0.0001555083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02610273,"about_ca_system_score_gemma":0.03637091,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9903545,"about_ca_topic_score_gemma":0.9940577,"domain_scores_codex":[0.9985729,0.0001884743,0.00004585221,0.000127044,0.0003289969,0.0007366866],"domain_scores_gemma":[0.9943375,0.00142669,0.001057458,0.0001358911,0.001121805,0.00192066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002344103,0.000128233,0.9729087,0.00003637977,0.0002085228,0.0002058124,0.001288374,0.003682632,0.000143451,0.006334186,0.003190682,0.01163845],"study_design_scores_gemma":[0.00006237889,0.00005841341,0.9726963,0.0001045023,0.0002834544,0.00006519906,0.01022257,0.009987389,0.0002373968,0.001865569,0.004362705,0.00005418177],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910215,0.0008842025,0.0001686908,0.002557409,0.00001684697,0.0000254476,0.0008488995,0.00001023733,0.004466682],"genre_scores_gemma":[0.9981483,0.0002577231,0.00008862698,0.0001536328,0.000005878365,0.000005526433,0.0003543761,0.000003902522,0.0009821801],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02610273,"threshold_uncertainty_score":0.1893895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04409578833213965,"score_gpt":0.2923271211915642,"score_spread":0.2482313328594245,"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."}}