{"id":"W4381250101","doi":"10.1111/capa.12532","title":"Spending reviews and the Government of Canada: From episodic to institutionalized capabilities and repertoires","year":2023,"lang":"en","type":"article","venue":"Canadian Public Administration","topic":"Public Policy and Administration Research","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Victoria","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Government (linguistics); Context (archaeology); Corporate governance; Government spending; Political science; Pandemic; Coronavirus disease 2019 (COVID-19); Public administration; Public relations; Economics; Geography; Finance; Welfare; Law; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.02542507,0.0002976444,0.0004593348,0.006621277,0.01401679,0.02110414,0.002270458,0.002644393,0.003662212],"category_scores_gemma":[0.07080327,0.0005675564,0.0003311757,0.009053566,0.01297149,0.00369372,0.004547156,0.002799643,0.000376741],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.1710849,"about_ca_system_score_gemma":0.3462805,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9548576,"about_ca_topic_score_gemma":0.9783179,"domain_scores_codex":[0.9612404,0.01261758,0.001481456,0.001938487,0.01479531,0.00792687],"domain_scores_gemma":[0.8105186,0.0394011,0.02037833,0.005843841,0.08275456,0.04110366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002168563,0.0001220187,0.06155599,0.001165577,0.000136409,0.001112997,0.07143728,0.001978334,0.001759479,0.2898822,0.344329,0.2263039],"study_design_scores_gemma":[0.00002537605,0.00007452277,0.07090448,0.001047882,0.00005298157,0.0001461291,0.0274111,0.0004798312,0.0005862775,0.008892633,0.8901349,0.0002438379],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2271585,0.02959707,0.004770739,0.4173421,0.001882615,0.0003696597,0.00159998,0.00061118,0.3166682],"genre_scores_gemma":[0.9388903,0.007265754,0.002363286,0.02109337,0.0003586778,0.000119909,0.0002283786,0.0001177017,0.02956255],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8289151,"threshold_uncertainty_score":0.961424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05713546310116428,"score_gpt":0.3264431685704439,"score_spread":0.2693077054692796,"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."}}