{"id":"W3173928792","doi":"10.1080/21622671.2021.1928540","title":"Towards smart regional growth: institutional complexities and the regional governance of Southern Ontario’s Greenbelt","year":2021,"lang":"en","type":"article","venue":"Territory Politics Governance","topic":"Rural development and sustainability","field":"Agricultural and Biological Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; Universiteit Utrecht","keywords":"Growth management; Corporate governance; Politics; Government (linguistics); Regional policy; Regional planning; Intervention (counseling); Business; Political science; Environmental planning; Public administration; Geography; Urban planning; Land use","routes":{"ca_aff":false,"ca_fund":true,"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":[0.001528058,0.0001280037,0.0001442601,0.0005729877,0.005687973,0.006171475,0.0007403867,0.0005279882,0.002797759],"category_scores_gemma":[0.002368917,0.0002031566,0.0001591509,0.001072984,0.01137932,0.001211488,0.002391527,0.0006091087,0.0001492082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07559885,"about_ca_system_score_gemma":0.06018785,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9443127,"about_ca_topic_score_gemma":0.98284,"domain_scores_codex":[0.9986959,0.0002564583,0.0000349281,0.0001490586,0.0002700081,0.0005936903],"domain_scores_gemma":[0.9984944,0.0002336138,0.0002769258,0.0001378824,0.0003717607,0.0004854094],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0000832791,0.00003588741,0.1083134,0.0002066525,0.0000496445,0.001547194,0.1431805,0.01420356,0.003080748,0.6794121,0.01124406,0.03864291],"study_design_scores_gemma":[0.00002999349,0.0000499141,0.301917,0.0003297084,0.00005672398,0.0002522427,0.2098677,0.006743219,0.001243351,0.0722955,0.4071226,0.00009211857],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7405188,0.001071218,0.006348663,0.01476811,0.00004079459,0.0001057603,0.0002429709,0.0000731548,0.2368306],"genre_scores_gemma":[0.9905723,0.0002411583,0.0006970121,0.0001002851,0.000003535642,0.00001003103,0.00003197208,0.000008631139,0.008335088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07559885,"threshold_uncertainty_score":0.5485106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02588105502565155,"score_gpt":0.2046545300732749,"score_spread":0.1787734750476233,"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."}}