{"id":"W2229611050","doi":"10.1111/ropr.12156","title":"Institutional Change Through Policy Learning: The Case of the European Commission and Research Policy","year":2016,"lang":"en","type":"article","venue":"Review of Policy Research","topic":"Policy Transfer and Learning","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada; European Commission; York University","keywords":"Framing (construction); Policy learning; European commission; Corporate governance; Foundation (evidence); Commission; Political science; Institutional change; Public administration; Research policy; Empirical research; Public relations; Business; Economics; Management; European union; Epistemology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.02199818,0.0001388028,0.0003061007,0.0004906527,0.002592116,0.00005107271,0.001086636,0.00008510794,0.00008590078],"category_scores_gemma":[0.02228002,0.00006654423,0.0001581881,0.003890064,0.005162931,0.0002539389,0.0006307065,0.0009555751,0.00004076077],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003573601,"about_ca_system_score_gemma":0.002981711,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1529133,"about_ca_topic_score_gemma":0.001146386,"domain_scores_codex":[0.9816793,0.01521903,0.0004379422,0.0002844002,0.001440678,0.0009386101],"domain_scores_gemma":[0.9959512,0.002329202,0.0001065155,0.0005904111,0.0007770709,0.0002456261],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001160901,0.00005266687,0.0006594654,0.001233289,0.00001983743,0.00001854116,0.01859789,2.651874e-7,0.000580247,0.7460724,0.002051394,0.2307024],"study_design_scores_gemma":[0.0003497104,0.0001235482,0.00633915,0.006427624,0.00001021635,0.00009621164,0.001777747,0.000002218707,0.0002251936,0.009427968,0.9750977,0.0001226903],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01730995,0.02360433,0.00001921692,0.383434,0.00004227466,0.001491775,0.00004457977,0.00003266554,0.5740212],"genre_scores_gemma":[0.8679938,0.1265994,0.00001267527,0.0004877444,0.002146238,0.00003634236,7.529072e-7,0.00001981203,0.002703136],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9730463,"threshold_uncertainty_score":0.9987064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4003690990395499,"score_gpt":0.5720726382239324,"score_spread":0.1717035391843825,"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."}}