{"id":"W3017512041","doi":"10.1080/13876988.2020.1762077","title":"Policy Learning in Comparative Policy Analysis","year":2020,"lang":"en","type":"article","venue":"Journal of Comparative Policy Analysis Research and Practice","topic":"Policy Transfer and Learning","field":"Social Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 European Research Council; Concordia University","keywords":"Policy learning; Causality (physics); Causation; Policy analysis; Set (abstract data type); Relation (database); Probabilistic logic; Computer science; Epistemology; Political science; Positive economics; Management science; Artificial intelligence; Machine learning; Economics; Public administration; Data mining; Law","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.06256527,0.00137087,0.002211771,0.005668417,0.003349417,0.007565407,0.002882035,0.004780916,0.008498809],"category_scores_gemma":[0.1168024,0.0006373446,0.001364309,0.006039279,0.02135677,0.01371708,0.006962668,0.005798556,0.0004280646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01367926,"about_ca_system_score_gemma":0.008368673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007922174,"about_ca_topic_score_gemma":0.005841218,"domain_scores_codex":[0.9413669,0.05094485,0.0009908585,0.002595906,0.002783707,0.001317737],"domain_scores_gemma":[0.8859208,0.1031282,0.002979958,0.005071973,0.002194947,0.0007040098],"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":[0.00001183776,0.00001519457,0.0002919355,0.00008466899,0.00002980262,0.0000206433,0.0001833756,0.01056397,0.00000900044,0.9813706,0.000343728,0.007075291],"study_design_scores_gemma":[0.000008437666,0.00000854581,0.000088873,0.0000801951,0.000005865842,0.00000734254,0.00009380112,0.007543417,0.00003711228,0.989627,0.002491753,0.000007741633],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0310118,0.02365728,0.7178104,0.05610916,0.00102292,0.0004461283,0.0003428517,0.0002664457,0.1693329],"genre_scores_gemma":[0.884503,0.007113222,0.09960771,0.002706923,0.0007666551,0.0006735797,0.0001387045,0.00008321934,0.004406856],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06256527,"threshold_uncertainty_score":0.3308807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3382077729965742,"score_gpt":0.5881449315568932,"score_spread":0.249937158560319,"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."}}