{"id":"W2038633574","doi":"10.1002/ev.1171","title":"Translating evaluation findings into “policy language”","year":2000,"lang":"en","type":"article","venue":"New Directions for Evaluation","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Affect (linguistics); Welfare; Order (exchange); Policy learning; Policy analysis; Program evaluation; Language policy; Computer science; Management science; Political science; Public administration; Sociology; Pedagogy; Economics; Machine learning; Law; Finance","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":[0.156343,0.0007346299,0.001301599,0.006424267,0.00250929,0.01765371,0.002182998,0.001788223,0.008775703],"category_scores_gemma":[0.3000719,0.0005081587,0.0006727458,0.004739382,0.00950209,0.007992976,0.005105081,0.005592985,0.001613213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02586271,"about_ca_system_score_gemma":0.05310005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03829459,"about_ca_topic_score_gemma":0.02790044,"domain_scores_codex":[0.819006,0.1429754,0.006996983,0.002139971,0.02665624,0.002225277],"domain_scores_gemma":[0.6446816,0.245495,0.006467561,0.01373955,0.08783863,0.001777791],"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":[0.0001413578,0.0003259135,0.002437763,0.0036428,0.0001479298,0.0002697577,0.01692639,0.005534031,0.001890888,0.6580023,0.07408161,0.2365994],"study_design_scores_gemma":[0.0002309244,0.0003251755,0.006708131,0.02674374,0.00029881,0.0001270104,0.04214897,0.008441988,0.01148432,0.3370012,0.5662746,0.0002152735],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02907343,0.01163706,0.2213113,0.3360745,0.008373706,0.001925659,0.002165633,0.001470447,0.3879682],"genre_scores_gemma":[0.6926892,0.02017939,0.2197573,0.03662055,0.001676575,0.002992674,0.001162451,0.0009087534,0.02401309],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.156343,"threshold_uncertainty_score":0.8268305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1976021849984889,"score_gpt":0.5590826968278899,"score_spread":0.3614805118294011,"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."}}