{"id":"W4379742513","doi":"10.1111/capa.12522","title":"Morality analysis: Reducing moral backlash to public policy","year":2023,"lang":"en","type":"article","venue":"Canadian Public Administration","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vale (Canada)","funders":"","keywords":"Morality; Backlash; Public policy; Incentive; Government (linguistics); Policy analysis; Political science; Public administration; Public economics; Law and economics; Economics; Sociology; Law; Computer science; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.1602502,0.001650135,0.001783338,0.007815852,0.006374401,0.0149416,0.003208706,0.005132645,0.01270223],"category_scores_gemma":[0.3149019,0.0009658424,0.001593084,0.003720141,0.0169771,0.009787572,0.01090142,0.009849865,0.0008776435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02059292,"about_ca_system_score_gemma":0.04481981,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008435458,"about_ca_topic_score_gemma":0.007229806,"domain_scores_codex":[0.8051317,0.159874,0.003295936,0.004502823,0.0224441,0.004751509],"domain_scores_gemma":[0.6231195,0.2965793,0.02663969,0.01344227,0.03460641,0.005612903],"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":[0.0003052442,0.0003846593,0.004655967,0.0008702612,0.0002680658,0.000167101,0.004907314,0.03342861,0.0005534081,0.7869946,0.01717342,0.1502914],"study_design_scores_gemma":[0.0001803256,0.0003112442,0.002885451,0.001599148,0.0001542146,0.00005747482,0.004115433,0.05487315,0.001621612,0.9025019,0.03153473,0.0001654289],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07824771,0.002508754,0.6020537,0.0962491,0.001401627,0.001984578,0.000306219,0.000911978,0.2163363],"genre_scores_gemma":[0.8636854,0.0007712228,0.1254702,0.004798146,0.0002875074,0.001093691,0.00007306126,0.0001515396,0.003669225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9915645,"threshold_uncertainty_score":0.8474941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3064809924406564,"score_gpt":0.4929595553286005,"score_spread":0.1864785628879441,"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."}}