{"id":"W4406963236","doi":"10.2139/ssrn.5115289","title":"Racial Disparity and Discrimination in Housing in Canada","year":2025,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Urbanization and City Planning","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Racism; Geography; Demographic economics; Political science; Economics; Law","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":[0.001048767,0.0001762658,0.000512887,0.002363154,0.009519118,0.00289924,0.001525844,0.001004785,0.006858845],"category_scores_gemma":[0.004390379,0.0002827225,0.0005560798,0.006050216,0.002061412,0.0007737936,0.002309101,0.001480044,0.0002993893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04308115,"about_ca_system_score_gemma":0.06576969,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9960901,"about_ca_topic_score_gemma":0.9984961,"domain_scores_codex":[0.9973618,0.0002252982,0.0001040954,0.0001783679,0.0005377856,0.00159258],"domain_scores_gemma":[0.9962184,0.0002236328,0.0005233592,0.00008159427,0.001388663,0.001564439],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002017379,0.0002101413,0.9578137,0.00005191005,0.0000776524,0.0002596094,0.01082306,0.0004096355,0.0001405323,0.008083722,0.005398134,0.01653023],"study_design_scores_gemma":[0.00001284576,0.00002691694,0.9728228,0.0001273901,0.00003181103,0.00007816894,0.01927316,0.0004366796,0.00007064885,0.0007006196,0.006389495,0.0000294972],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836731,0.001370772,0.00006775091,0.002842744,0.00005770055,0.00002020468,0.0008490816,0.000005017556,0.01111359],"genre_scores_gemma":[0.9974596,0.0003625302,0.00003566894,0.0001524364,0.00000915311,0.000004133609,0.0001652292,0.000003547691,0.001807725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04308115,"threshold_uncertainty_score":0.3125771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00736438258805172,"score_gpt":0.2628781778495512,"score_spread":0.2555137952614995,"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."}}