{"id":"W3126014099","doi":"","title":"Political Uncertainty and the Earmarking of Environmental Taxes","year":2001,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Allison University","funders":"","keywords":"Dividend; Economics; Politics; Revenue; Public economics; Tax revenue; Finance; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005343051,0.0001927592,0.0004552066,0.0007972083,0.001968997,0.005137005,0.000395447,0.002159383,0.003233408],"category_scores_gemma":[0.03255976,0.0002551198,0.0002783349,0.0008442513,0.003739632,0.003810694,0.001927228,0.002945545,0.0002570201],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003050741,"about_ca_system_score_gemma":0.001229637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002285437,"about_ca_topic_score_gemma":0.002273486,"domain_scores_codex":[0.9963685,0.001520259,0.0001428327,0.0003023952,0.0008809291,0.0007849243],"domain_scores_gemma":[0.9788407,0.01321685,0.00559856,0.0008139416,0.0008963699,0.0006335538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0001921596,0.00006864232,0.00961097,0.00005978657,0.00004100001,0.0003588657,0.001261657,0.01905656,0.0005540097,0.9475235,0.002387765,0.01888495],"study_design_scores_gemma":[0.00003194828,0.00005010213,0.009291624,0.00004549426,0.00003271152,0.0001168196,0.00107705,0.01547564,0.0009684762,0.9626434,0.01022402,0.0000426788],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7449709,0.004220179,0.03836615,0.03297931,0.0002214592,0.00004398347,0.0002061997,0.00007278356,0.1789189],"genre_scores_gemma":[0.9980403,0.0002963475,0.0002603706,0.000232731,0.00004726783,0.000005330222,0.000009113985,0.000003748696,0.001104914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005343051,"threshold_uncertainty_score":0.02825707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01119227129196588,"score_gpt":0.1938258965933317,"score_spread":0.1826336253013658,"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."}}