{"id":"W4206182038","doi":"10.31235/osf.io/edxju","title":"Generational differences in income trajectories in the Nordic welfare state","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Psychological Well-being and Life Satisfaction","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Demographic economics; Economic inequality; Economics; Welfare state; Inequality; Welfare; Falling (accident); Total personal income; Income distribution; Population; Income inequality metrics; Quarter (Canadian coin); Labour economics; Demography; Sociology; Geography; Gross income; Political science; Psychology; Public economics","routes":{"ca_aff":false,"ca_fund":false,"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":[0.0005699669,0.0001047995,0.0001579252,0.0007115955,0.0006182693,0.0009191083,0.0001764673,0.0001974755,0.001210919],"category_scores_gemma":[0.001431934,0.00009946191,0.0002620816,0.0007890941,0.0002853008,0.0003620599,0.0007927608,0.0003567121,0.0001436008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005315611,"about_ca_system_score_gemma":0.0005866166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05524126,"about_ca_topic_score_gemma":0.07160921,"domain_scores_codex":[0.9997728,0.0000633762,0.00001161963,0.00005819705,0.00002124254,0.00007282822],"domain_scores_gemma":[0.999546,0.0001221056,0.0001408717,0.0000439527,0.0000709616,0.00007607479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001768887,0.00005965403,0.9858936,0.00001193085,0.00007083497,0.0002184455,0.002954557,0.0006753979,0.0001903582,0.0008822746,0.0005050377,0.008361075],"study_design_scores_gemma":[0.000002618066,0.00002352757,0.9961778,0.00001726287,0.00001513846,0.00004026157,0.002453246,0.0003559928,0.0000493059,0.0002795875,0.0005793273,0.000005976307],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986766,0.0001232796,0.00007014113,0.00005014678,0.00000449267,0.000003154953,0.0003482181,0.000001614108,0.0007223085],"genre_scores_gemma":[0.9988109,0.0001162407,0.00006325884,0.00000843214,0.000001607823,0.000003582788,0.0004964231,0.000001515732,0.000497909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05524126,"threshold_uncertainty_score":0.1098394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04839808378977716,"score_gpt":0.3333958034446814,"score_spread":0.2849977196549043,"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."}}