{"id":"W1570315903","doi":"","title":"Fiscal transfer in Canada: Drawing comparisons and lessons","year":2004,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Local Government Finance and Decentralization","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Macro; Revenue; Per capita; Economics; Relevance (law); Public economics; Service (business); Tax revenue; Transfer (computing); Fiscal policy; Fiscal system; Per capita income; Macroeconomics; Economic policy; Finance; Political science; Economy; Computer science; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009764508,0.0001438134,0.0003279692,0.0001254651,0.0002198496,0.0001151752,0.0003153604,0.0002437532,0.00004734297],"category_scores_gemma":[0.0001710955,0.0001692674,0.00004277834,0.0001351724,0.0002792504,0.0001003136,0.0001973582,0.0008823945,0.000001111287],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.006293083,"about_ca_system_score_gemma":0.005859762,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8419432,"about_ca_topic_score_gemma":0.9942446,"domain_scores_codex":[0.9978468,0.0002298926,0.0003672614,0.0004905537,0.0003845058,0.0006809747],"domain_scores_gemma":[0.9993252,0.0002236083,0.00004010035,0.000223264,0.00002622425,0.0001616215],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001159631,0.0002600187,0.724315,0.000219833,0.00005413085,0.0001346919,0.01374733,0.06998579,0.00001693951,0.04749363,0.000378987,0.1432776],"study_design_scores_gemma":[0.002628773,0.00006223089,0.7850016,0.001231209,0.00001845573,0.000002603542,0.03183193,0.01271979,0.0001338233,0.008146085,0.1568517,0.001371839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9184161,0.0002108203,0.00004766929,0.004705965,0.0003309399,0.0006335035,0.00005731546,0.00001429764,0.07558338],"genre_scores_gemma":[0.9870341,0.01237352,0.00004616201,0.00008526954,0.00007605657,0.0000461017,0.00001686056,0.00001514017,0.0003067896],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1564727,"threshold_uncertainty_score":0.9997761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04765760548525019,"score_gpt":0.3322908263475129,"score_spread":0.2846332208622627,"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."}}