{"id":"W3006582453","doi":"10.1177/0739456x20904427","title":"Tracing Discretion in Planning and Land-Use Outcomes: Perspectives from Toronto, Canada","year":2020,"lang":"en","type":"article","venue":"Journal of Planning Education and Research","topic":"Urban Planning and Governance","field":"Social Sciences","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Discretion; Zoning; Accountability; Politics; Land-use planning; Land use; Context (archaeology); Public administration; Local planning; Democracy; Urban planning; Business; Public participation; Public economics; Political science; Environmental planning; Economics; Law; Geography; Engineering; Civil engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007678173,0.00005375497,0.0001325703,0.00005588756,0.0002373278,0.0001440456,0.00009000322,0.0000448652,0.00002524823],"category_scores_gemma":[0.001154787,0.0000444535,0.00001365004,0.0001261166,0.0000722321,0.0004372936,0.00001312622,0.0003453763,2.226013e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002444953,"about_ca_system_score_gemma":0.001079328,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6260153,"about_ca_topic_score_gemma":0.1903013,"domain_scores_codex":[0.9988453,0.0002233082,0.0001729401,0.0001154565,0.0004737212,0.0001692788],"domain_scores_gemma":[0.9989748,0.0005533348,0.0001084437,0.00003371878,0.0001393083,0.0001903792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004524988,0.00002634406,0.7723244,0.000008149854,0.0000117357,0.00001896367,0.2200444,0.00005364059,0.00003411541,0.0001102909,0.006124386,0.001198353],"study_design_scores_gemma":[0.0002123215,0.00004407195,0.7911217,0.0002472548,0.000004270537,0.000003208699,0.1898132,0.00009417945,0.0000068857,0.00005354055,0.0183351,0.00006437904],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838701,0.007577737,0.00003987824,0.007306585,0.0001767528,0.00005131495,0.000006284596,0.000003891285,0.0009674585],"genre_scores_gemma":[0.9986538,0.0002265737,0.0002257449,0.0001446068,0.0003143497,0.000001031631,0.00000166079,0.000004257151,0.000428025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.435714,"threshold_uncertainty_score":0.8244736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09532864688384377,"score_gpt":0.4242910132128354,"score_spread":0.3289623663289917,"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."}}