{"id":"W3031036335","doi":"10.3138/cjpe.61624","title":"Evaluation in the Provinces and Territories: A Cross-Canada Snapshot and Call to Action","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Program Evaluation","topic":"Evaluation and Performance Assessment","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island; University of Victoria; Université Laval; Dalhousie University","funders":"","keywords":"Snapshot (computer storage); Government (linguistics); Public administration; Political science; State (computer science); Action (physics); Regional science; Public relations; Geography; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05635059,0.0005378946,0.001121044,0.005645671,0.01425684,0.01376007,0.003185012,0.002543333,0.002950712],"category_scores_gemma":[0.05904572,0.0007514249,0.0009912084,0.01275945,0.005417013,0.00420319,0.006632069,0.00413206,0.0002387699],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.2925023,"about_ca_system_score_gemma":0.586039,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.990824,"about_ca_topic_score_gemma":0.9962059,"domain_scores_codex":[0.9490002,0.01601022,0.003698105,0.001720218,0.01632179,0.01324944],"domain_scores_gemma":[0.7930371,0.04012758,0.006186914,0.004893066,0.1270563,0.02869899],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001023776,0.000521581,0.2082412,0.01175801,0.0006445058,0.002074824,0.05047722,0.002960288,0.002364677,0.04154947,0.1519759,0.5264086],"study_design_scores_gemma":[0.00009964994,0.0003077618,0.5015734,0.01245191,0.0003755887,0.0006223627,0.1320261,0.001800408,0.001543741,0.003332759,0.3455136,0.0003526558],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2814589,0.1789132,0.005042935,0.4426525,0.002147191,0.002491848,0.007773884,0.0004220696,0.07909746],"genre_scores_gemma":[0.8865341,0.05943068,0.0189022,0.02081966,0.0001412711,0.0006580315,0.002725214,0.000100485,0.01068836],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9436494,"threshold_uncertainty_score":0.8205971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4273514882657697,"score_gpt":0.5421958438593792,"score_spread":0.1148443555936096,"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."}}