{"id":"W7029052588","doi":"","title":"Home for whom? A socio-political examination of Montreal's bylaw for a diverse metropolis","year":2021,"lang":"en","type":"other","venue":"eScholarship@McGill (McGill)","topic":"History of Computing Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Work (physics); Diversity (politics); Data collection","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":[0.001584542,0.0003468182,0.0002592069,0.001492281,0.05234283,0.01148684,0.002144146,0.003104817,0.01719232],"category_scores_gemma":[0.003353753,0.0004308788,0.0002888784,0.003427852,0.01233094,0.002847021,0.003780451,0.005198943,0.0005171882],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09007747,"about_ca_system_score_gemma":0.06871646,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9857471,"about_ca_topic_score_gemma":0.9963744,"domain_scores_codex":[0.9978337,0.0004725717,0.00001534073,0.00013376,0.0003211911,0.001223441],"domain_scores_gemma":[0.9979235,0.0003377815,0.0001401466,0.00006075253,0.0004524773,0.001085289],"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":[0.00008625702,0.00009802111,0.01780165,0.00007732472,0.00003374592,0.001685241,0.1943756,0.0004175747,0.0006992547,0.5786734,0.1791469,0.02690494],"study_design_scores_gemma":[0.00001882103,0.00003937259,0.06067768,0.0001624849,0.0000223107,0.0001143099,0.2294428,0.0003931033,0.0002627494,0.007121366,0.7016543,0.00009073172],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3506033,0.003944027,0.0007701025,0.1682463,0.0006578728,0.0001453862,0.0007635476,0.00006589996,0.4748037],"genre_scores_gemma":[0.8638103,0.0009028026,0.000250731,0.006852673,0.0001044102,0.00004454569,0.0000858757,0.00005342303,0.1278952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09007747,"threshold_uncertainty_score":0.6535609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02638202788307749,"score_gpt":0.251700797154345,"score_spread":0.2253187692712675,"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."}}