{"id":"W2606199036","doi":"10.1017/s0008423915000529","title":"Spending on Political Staffers and the Revealed Preferences of Cabinet: Examining a New Data Source on Federal Political Staff in Canada","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Political Science","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Cabinet (room); Staffing; Politics; Variance (accounting); Government (linguistics); Test (biology); Construct (python library); Public administration; Public relations; Political science; Business; Computer science; Accounting; Engineering; Law","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":[0.003779284,0.0002669801,0.0005559511,0.004046747,0.003116663,0.002070297,0.00128778,0.0003371414,0.002900896],"category_scores_gemma":[0.01951513,0.0002586098,0.0003626672,0.01194788,0.0009414115,0.0007306496,0.001114408,0.000981084,0.0002595767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04431939,"about_ca_system_score_gemma":0.05168756,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9964051,"about_ca_topic_score_gemma":0.9974971,"domain_scores_codex":[0.9969859,0.0004581085,0.000168689,0.0002505375,0.001363322,0.0007735611],"domain_scores_gemma":[0.972626,0.007726914,0.004534969,0.001274555,0.01192414,0.001913432],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002177028,0.0001176521,0.966453,0.00006990263,0.0001130746,0.0001309331,0.004487213,0.004012745,0.0002467067,0.003206284,0.00606656,0.0148784],"study_design_scores_gemma":[0.00001361041,0.0000262292,0.9802583,0.00006029809,0.00003245051,0.00002630902,0.00541859,0.005949049,0.0003580335,0.0002701347,0.007544806,0.00004209794],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855762,0.0002464317,0.0004568695,0.00063611,0.000007424927,0.00002991937,0.00994718,0.00001770492,0.003082223],"genre_scores_gemma":[0.9894696,0.0001719525,0.0005006255,0.00005714139,0.000005263506,0.00002397084,0.007713194,0.0000108273,0.002047357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04431939,"threshold_uncertainty_score":0.3215612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1378658196922868,"score_gpt":0.2623901081226596,"score_spread":0.1245242884303729,"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."}}