{"id":"W2538718045","doi":"10.3138/9781442685468-015","title":"13. Is IT Transforming Government? Evidence and Lessons from Canada","year":2007,"lang":"en","type":"book-chapter","venue":"University of Toronto Press eBooks","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Political science; Business; Philosophy; Linguistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006393871,0.0004930323,0.0006731006,0.003470344,0.01026158,0.01096311,0.002062413,0.004823265,0.02914097],"category_scores_gemma":[0.03966228,0.0003785304,0.0005698758,0.01382286,0.007544241,0.004756215,0.003185411,0.004058083,0.00146981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08257584,"about_ca_system_score_gemma":0.2569777,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9921741,"about_ca_topic_score_gemma":0.9967919,"domain_scores_codex":[0.9901192,0.001367294,0.0003958818,0.0004881339,0.004136272,0.003493184],"domain_scores_gemma":[0.9662941,0.01530748,0.001442848,0.001165211,0.01287963,0.002910683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003216648,0.0001597102,0.05007416,0.002592236,0.000115868,0.0008999038,0.02751121,0.0008584887,0.0001364417,0.3799058,0.3844242,0.1530003],"study_design_scores_gemma":[0.0002538193,0.0000858574,0.2056835,0.009815885,0.0005371597,0.0002110796,0.09695318,0.0005557623,0.0005744777,0.03907303,0.6461245,0.00013169],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05880776,0.03728437,0.000479378,0.2179853,0.0007213115,0.0001898434,0.00678937,0.00006621516,0.6776764],"genre_scores_gemma":[0.7713292,0.07123057,0.001249104,0.05512773,0.000313962,0.0002020455,0.002951954,0.0001199972,0.09747531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08257584,"threshold_uncertainty_score":0.5991325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05761264728237289,"score_gpt":0.2616603655668573,"score_spread":0.2040477182844845,"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."}}