{"id":"W2907054267","doi":"10.1007/s00148-018-0726-8","title":"Government Transfers, Work, and Wellbeing: Evidence from the Russian Old-Age Pension","year":2019,"lang":"en","type":"article","venue":"Journal of Population Economics","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University; Blackberry (Canada); University of Guelph","funders":"Universität Mannheim; Acadia University","keywords":"Receipt; Pension; Labour economics; Economics; Government (linguistics); Social policy; Work (physics); Demographic economics; Production (economics); Business; Market economy; Macroeconomics; Finance","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001475923,0.0002732362,0.0004560782,0.00146735,0.0007364191,0.0007799593,0.0004018546,0.0004451206,0.003023967],"category_scores_gemma":[0.003052743,0.0001631273,0.0005745789,0.001931644,0.0006298291,0.000473661,0.001170312,0.0005009825,0.0003922038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004686331,"about_ca_system_score_gemma":0.0006402225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03751637,"about_ca_topic_score_gemma":0.03848444,"domain_scores_codex":[0.9995753,0.0001508775,0.0000461862,0.00004995395,0.00006658129,0.0001110267],"domain_scores_gemma":[0.9976922,0.0008581018,0.0007675033,0.0001745905,0.0002661268,0.0002414024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000415324,0.0002048755,0.9879189,0.00009296156,0.0002914621,0.0002067969,0.002467853,0.0001213414,0.0002082698,0.0005105934,0.0004686768,0.007092951],"study_design_scores_gemma":[0.000007879993,0.00006095657,0.9966935,0.00003156127,0.0001396329,0.0000390672,0.002046433,0.00004427505,0.0000406405,0.00007296834,0.0008195468,0.00000347154],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972985,0.0009364624,0.00003468783,0.0001157586,0.000007807898,0.00000397678,0.0004290071,6.789338e-7,0.001173025],"genre_scores_gemma":[0.9977272,0.001075972,0.0000211538,0.00002868679,0.0000135944,0.00000425361,0.0005595151,9.54051e-7,0.0005687258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03751637,"threshold_uncertainty_score":0.07459599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714087263421391,"score_gpt":0.2072230379257926,"score_spread":0.1900821652915787,"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."}}