{"id":"W1606845909","doi":"","title":"GINI Country Report: Growing Inequalities and their Impacts in Canada","year":2013,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Canadian Policy and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Gini coefficient; Inequality; Redistribution (election); Economics; Income distribution; Economic inequality; Distribution (mathematics); Debt; Demographic economics; Government (linguistics); Household income; Development economics; Labour economics; Geography; Political science; Macroeconomics; Politics","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":[0.001708101,0.0007070859,0.0005565412,0.004652676,0.00291631,0.003098374,0.001148075,0.0007729082,0.008308703],"category_scores_gemma":[0.006959836,0.000389898,0.0009015373,0.01610142,0.0007029253,0.000880064,0.00160467,0.002683355,0.0007768499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05711007,"about_ca_system_score_gemma":0.1176035,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9966913,"about_ca_topic_score_gemma":0.9965762,"domain_scores_codex":[0.9971365,0.00009899759,0.0000937191,0.0001567833,0.001832962,0.0006811201],"domain_scores_gemma":[0.9938747,0.0002469606,0.0004528978,0.0001278645,0.004473767,0.0008237086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00009935511,0.00003007055,0.09551108,0.0005333234,0.0001659598,0.0001820497,0.0008235372,0.001453442,0.0001070378,0.02069635,0.8238449,0.05655309],"study_design_scores_gemma":[0.0000581041,0.00002166461,0.5112514,0.000891063,0.0001880195,0.0001491805,0.001299973,0.002250462,0.0003291097,0.002098611,0.4813643,0.0000981018],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.06983662,0.04224511,0.002135596,0.06406262,0.002776354,0.0003727192,0.6760853,0.0008685444,0.1416171],"genre_scores_gemma":[0.4491738,0.0711054,0.006377052,0.006902498,0.001241956,0.000396491,0.3762184,0.0007650948,0.08781934],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05711007,"threshold_uncertainty_score":0.4143645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.034466380630792,"score_gpt":0.3145811830691675,"score_spread":0.2801148024383756,"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."}}