{"id":"W3124505989","doi":"","title":"Push and Pull: Disability Insurance, Regional Labor Markets, and Benefit Generosity in Canada and the United States","year":2017,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Employment and Social Development Canada","keywords":"Generosity; Disability insurance; Economics; Labour economics; Demographic economics; Instrumental variable; Health insurance; Disability benefits; Economic growth; Political science; Social security; Health care; Market economy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002049803,0.0002960468,0.0007834738,0.001727031,0.003190108,0.003235734,0.00108432,0.0008498192,0.005277954],"category_scores_gemma":[0.007256757,0.0001813908,0.0007496282,0.003699541,0.002152137,0.001004216,0.00237024,0.001569375,0.0001899708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02733968,"about_ca_system_score_gemma":0.03808431,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9916143,"about_ca_topic_score_gemma":0.9938319,"domain_scores_codex":[0.9987476,0.0001535138,0.00003871835,0.0001179446,0.0003111321,0.0006310821],"domain_scores_gemma":[0.9943902,0.001567111,0.0009418853,0.000148119,0.001195916,0.001756651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000378715,0.0001819827,0.9403017,0.00007579871,0.000310347,0.0003377445,0.002805141,0.00607223,0.0002485555,0.01706112,0.008837423,0.02338929],"study_design_scores_gemma":[0.00009400463,0.00006528947,0.9567561,0.0001618359,0.0003947859,0.00007186165,0.01492365,0.01252138,0.0003435452,0.005260978,0.009321676,0.00008491988],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836366,0.001748129,0.0003251489,0.005034304,0.00003060718,0.00003162948,0.001360038,0.00001676879,0.007816768],"genre_scores_gemma":[0.9968636,0.000488786,0.0001356053,0.0002301851,0.00001099362,0.000007165318,0.0005273751,0.000007135709,0.001729169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02733968,"threshold_uncertainty_score":0.1983642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1088359934554783,"score_gpt":0.3760560576892018,"score_spread":0.2672200642337234,"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."}}