{"id":"W2064945112","doi":"","title":"The Sentencing Theory Debate: Convergence in Outcomes, Divergence in Reasoning","year":2007,"lang":"en","type":"article","venue":"TSpace (University of Toronto)","topic":"Criminal Justice and Corrections Analysis","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; University of Toronto","funders":"","keywords":"Retributive justice; Sentencing guidelines; Suspect; Deterrence (psychology); Limiting; Law; Criminal law; Criminal justice; Political science; Law and economics; Divergence (linguistics); Convergence (economics); Criminology; Economic Justice; Sociology; Philosophy; Economics; Engineering; Sentence","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":[0.09291542,0.000536097,0.001844534,0.005307234,0.008893545,0.02246592,0.005972913,0.01450192,0.004927642],"category_scores_gemma":[0.1400257,0.0005664517,0.001701625,0.003988551,0.05240704,0.02669312,0.01187783,0.0190101,0.0006180916],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02285491,"about_ca_system_score_gemma":0.01220924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01022834,"about_ca_topic_score_gemma":0.007753504,"domain_scores_codex":[0.906446,0.06769099,0.003001539,0.005212056,0.01323599,0.00441355],"domain_scores_gemma":[0.8812213,0.09819645,0.002831383,0.00750779,0.008328003,0.00191507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000007061573,0.000003845643,0.00009824282,0.00001157684,0.000003283589,0.00001818603,0.001509339,0.000223672,0.000007665317,0.9945476,0.0008664283,0.002703215],"study_design_scores_gemma":[0.000006924484,0.000004910297,0.0001991222,0.0000617179,0.000003977822,0.00001738575,0.00104188,0.0008808196,0.0000618474,0.9927862,0.00492641,0.000008723758],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.07500712,0.008570152,0.1290645,0.4315485,0.001316015,0.0001040795,0.000290151,0.0001565467,0.353943],"genre_scores_gemma":[0.9732779,0.00108042,0.01282266,0.006801312,0.0007018154,0.0001618224,0.00007277844,0.00009163978,0.004989582],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09291542,"threshold_uncertainty_score":0.4913896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01551193539464119,"score_gpt":0.2845585421156001,"score_spread":0.2690466067209589,"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."}}