{"id":"W2942954432","doi":"10.3386/w24830","title":"Financial Incentives and Earnings of Disability Insurance Recipients: Evidence from a Notch Design","year":2018,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; University of Calgary; HEC Montréal","funders":"Austrian Science Fund; Australian Government; National Institute on Aging; U.S. Social Security Administration","keywords":"Earnings; Incentive; Disability insurance; Economics; Liability; Earnings response coefficient; Business; Labour economics; Finance; Microeconomics; Social security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0162356,0.0002713566,0.0004379187,0.0008102047,0.0005715431,0.001263803,0.0008269642,0.0007866675,0.008277381],"category_scores_gemma":[0.03154874,0.0001953762,0.0006379313,0.0007615072,0.001159928,0.0007835661,0.001456691,0.0007105495,0.00105668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000415897,"about_ca_system_score_gemma":0.000470883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003290324,"about_ca_topic_score_gemma":0.003298452,"domain_scores_codex":[0.9926214,0.005071741,0.0004133398,0.0007028298,0.000762111,0.0004285117],"domain_scores_gemma":[0.9548604,0.02384752,0.01470541,0.004496993,0.001102496,0.0009871038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007974947,0.003160162,0.9101272,0.000301563,0.001014181,0.0001825714,0.001180715,0.001368458,0.0005604294,0.009304493,0.004808935,0.06001622],"study_design_scores_gemma":[0.001183931,0.005980325,0.9487339,0.0004233388,0.001588746,0.0002587928,0.002536611,0.009334074,0.002295592,0.01402584,0.01356691,0.00007205179],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989935,0.0005762827,0.002451104,0.0003382972,0.00003334093,0.0001661719,0.001883316,0.00001524256,0.004601303],"genre_scores_gemma":[0.9956951,0.0001972095,0.0007968025,0.0002972871,0.00002697744,0.00009917081,0.0006958838,0.000005640215,0.002185861],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0162356,"threshold_uncertainty_score":0.08586311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7256095196680232,"score_gpt":0.6023561258018162,"score_spread":0.123253393866207,"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."}}