{"id":"W7132996857","doi":"","title":"Between Public Goals and Private Projects: Negotiating Community Benefits for Density from Toronto&apos;s Urban Redevelopment","year":2017,"lang":"","type":"dissertation","venue":"TSpace","topic":"Urban Planning and Governance","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Land-use planning; Urban planning; Negotiation; Corporate governance; Land use; Regional planning; Discretion; Transportation planning; Redevelopment; Equity (law)","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":[0.00233627,0.0002151019,0.0001886817,0.0005087155,0.009539541,0.005771457,0.000833876,0.0009419925,0.008317438],"category_scores_gemma":[0.00422774,0.0003655958,0.0002157056,0.00083683,0.00606529,0.001983355,0.004925494,0.001099476,0.0003622247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05279072,"about_ca_system_score_gemma":0.04703307,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5810668,"about_ca_topic_score_gemma":0.8735017,"domain_scores_codex":[0.9974904,0.0009094096,0.0000522402,0.0001717557,0.0006904778,0.0006857301],"domain_scores_gemma":[0.9975915,0.0009013651,0.0001566194,0.0001619634,0.000347489,0.000841081],"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":[0.00009881058,0.00005147477,0.01259428,0.0001838859,0.00002239525,0.001436043,0.2535191,0.006661953,0.001605006,0.6195971,0.0332956,0.07093424],"study_design_scores_gemma":[0.00003231868,0.0001048827,0.02984778,0.0003979377,0.0000362723,0.0002418726,0.2689087,0.006029118,0.00126015,0.06229302,0.630767,0.00008095338],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4978202,0.0009156579,0.0108668,0.01232735,0.0001083477,0.0002224137,0.0001914796,0.00007191795,0.4774758],"genre_scores_gemma":[0.9699866,0.0002615374,0.001908434,0.0001558468,0.000009375353,0.00004609899,0.00004006769,0.0000176323,0.02757444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4189332,"threshold_uncertainty_score":0.8428008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1380181016186012,"score_gpt":0.4017111427168851,"score_spread":0.263693041098284,"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."}}