{"id":"W3123766534","doi":"","title":"In Front of and Behind the Veil of Ignorance: An Analysis of Motivations for Redistribution","year":2016,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université du Québec à Montréal","keywords":"Redistribution (election); Luck; Ignorance; Redistribution of income and wealth; Social psychology; Equity (law); Survey data collection; Psychology; Economics; Demographic economics; Political science; Microeconomics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.004029247,0.0002455029,0.0003564215,0.0004315778,0.000887728,0.001698207,0.000454549,0.001142676,0.007047349],"category_scores_gemma":[0.01752637,0.0002532302,0.0003191008,0.000239664,0.001634915,0.001380899,0.001130408,0.001308517,0.0003275237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005360536,"about_ca_system_score_gemma":0.0003805368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006107824,"about_ca_topic_score_gemma":0.0006968168,"domain_scores_codex":[0.9984441,0.001132626,0.00003654433,0.0001572394,0.0001237426,0.0001056509],"domain_scores_gemma":[0.9727328,0.0213143,0.003385561,0.001337171,0.0004256605,0.0008044945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.01172344,0.01452672,0.591915,0.001115001,0.0005492204,0.001497537,0.05120029,0.008742564,0.07631653,0.1458259,0.004178056,0.09240982],"study_design_scores_gemma":[0.002599519,0.008831359,0.6429279,0.0002395327,0.0005136028,0.001235629,0.05953083,0.05440104,0.01877469,0.1885143,0.02204516,0.0003865398],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930516,0.00005697972,0.001961666,0.0003495851,0.000007187497,0.00004323683,0.00004576869,0.000009252616,0.00447464],"genre_scores_gemma":[0.9976949,0.00003260779,0.001263189,0.0001084857,0.000005133128,0.00006702819,0.00003503293,0.000007039217,0.0007865962],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007047349,"threshold_uncertainty_score":0.02357572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02834157733648742,"score_gpt":0.3083412806432556,"score_spread":0.2799997033067682,"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."}}