{"id":"W4250077765","doi":"10.32920/ryerson.14656893.v1","title":"Placemaking &amp; Engaging Diverse Communities: Exploring Opportunities for Community Arts in Toronto’s Mobility Hubs","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Public Spaces through Art","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Community design; Neighbourhood (mathematics); Transformative learning; Community engagement; Urban planning; The arts; Built environment; Public relations; Sociology; Recreation; Urban sprawl; Urban design; Community building; Sense of community; Political science; Engineering; Civil engineering; Social science","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":[0.001688709,0.0003467138,0.0001942231,0.0009182172,0.01595308,0.004983137,0.001029204,0.001004276,0.005694],"category_scores_gemma":[0.001601199,0.0002450583,0.0002861545,0.0009282783,0.01090726,0.002077687,0.007681899,0.001259743,0.0002399665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01095983,"about_ca_system_score_gemma":0.01032235,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1993027,"about_ca_topic_score_gemma":0.6481472,"domain_scores_codex":[0.9983827,0.0008972427,0.00001988214,0.0000914486,0.0001716692,0.0004371365],"domain_scores_gemma":[0.9988412,0.0004846145,0.00007209589,0.00005517587,0.0000600952,0.0004867846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002687562,0.0000347392,0.002958708,0.0001234957,0.000005592487,0.001594738,0.9665502,0.0002144602,0.0009217881,0.01012286,0.002446966,0.01499962],"study_design_scores_gemma":[0.000004164749,0.0000283335,0.003971546,0.00008103973,0.000004465908,0.0001515945,0.9527068,0.000146316,0.0002036585,0.001156008,0.04153791,0.000008192438],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9187522,0.0006405472,0.002840938,0.003630545,0.00009582233,0.0001621311,0.00008873433,0.00003404785,0.07375512],"genre_scores_gemma":[0.9892939,0.00029086,0.001072146,0.0001600499,0.00001044567,0.00004261015,0.00002008257,0.00001299174,0.009096934],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8006973,"threshold_uncertainty_score":0.3962852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5565334058840582,"score_gpt":0.4285982562670085,"score_spread":0.1279351496170497,"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."}}