{"id":"W7132883632","doi":"","title":"Climate Data Practices in Toronto&apos;s Municipal Government","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Sustainability and Climate Change Governance","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ministry of the Environment, Conservation and Parks","funders":"","keywords":"Climate governance; Climate change; Government (linguistics); Corporate governance; Reflexivity; Thematic analysis; Climate justice; Declaration; Local government","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":[0.01183736,0.0001804024,0.0002867324,0.001356696,0.01787364,0.008726431,0.001350671,0.001364124,0.001830464],"category_scores_gemma":[0.01865885,0.0004313329,0.0001991733,0.007565138,0.01929645,0.002338017,0.006131513,0.001714094,0.0001411391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1011988,"about_ca_system_score_gemma":0.0831378,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8658468,"about_ca_topic_score_gemma":0.9360453,"domain_scores_codex":[0.9834843,0.008423875,0.0009171273,0.001220977,0.003642619,0.002311027],"domain_scores_gemma":[0.9764031,0.01120722,0.00259565,0.002675369,0.003579409,0.00353928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003019847,0.00003123326,0.02411042,0.0002111196,0.0000164244,0.0008410215,0.8737977,0.0006171719,0.001299554,0.05697499,0.007387563,0.03468263],"study_design_scores_gemma":[0.000009473421,0.00005755015,0.05172622,0.0002229182,0.00001404033,0.0001281578,0.7662734,0.0006374117,0.0007495215,0.003226147,0.1769039,0.00005125837],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9092001,0.002766547,0.002597251,0.02791082,0.00009640154,0.0002152377,0.0003838705,0.00009821686,0.0567316],"genre_scores_gemma":[0.9919752,0.0007411239,0.001045929,0.0005322014,0.000008188455,0.0000695803,0.00007782375,0.00001613682,0.005533806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1341532,"threshold_uncertainty_score":0.734252,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1393687271202432,"score_gpt":0.451290660332244,"score_spread":0.3119219332120008,"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."}}