{"id":"W2039043721","doi":"10.1353/dem.2000.0003","title":"The spatial separation of the poor in Canadian cities","year":2000,"lang":"en","type":"article","venue":"Demography","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Separation (statistics); Census; Geography; Index of dissimilarity; Ethnic group; Redevelopment; Population; Socioeconomics; Demography; Economic growth; Sociology; Political science; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003062739,0.00004477045,0.00006274505,0.00006641512,0.0007937851,0.00003372725,0.0001631792,0.00003740727,0.0001510822],"category_scores_gemma":[0.00004973805,0.00002738236,0.00006577692,0.0005251026,0.0003701192,0.00005714448,0.000005194569,0.00005406867,0.000006588004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002504271,"about_ca_system_score_gemma":0.0001608876,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6535847,"about_ca_topic_score_gemma":0.9808575,"domain_scores_codex":[0.9992797,0.0001369296,0.0001217031,0.00006859408,0.0001916827,0.0002013251],"domain_scores_gemma":[0.9996759,0.0001150641,0.00003371371,0.00008845545,0.00004255861,0.00004435913],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009197177,0.00001082174,0.9240258,0.000001637441,0.00002305685,3.839167e-7,0.02180918,0.00001888732,0.000003748339,0.02666372,0.008143675,0.01928984],"study_design_scores_gemma":[0.00009206969,0.000008551704,0.5818344,0.000005863442,0.000006027774,7.295698e-8,0.004023102,0.00005569378,0.00001808755,0.002719481,0.4111839,0.00005273423],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7544649,0.0007129072,0.00000473279,0.007108966,0.0003137771,0.0002440886,0.00001705594,0.00001575315,0.2371178],"genre_scores_gemma":[0.9976768,0.0002859285,0.00000511296,0.0002173313,0.0000819386,0.00001106031,0.000001028924,0.000002357204,0.001718474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4030402,"threshold_uncertainty_score":0.6105234,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01072581918013582,"score_gpt":0.268560114844084,"score_spread":0.2578342956639482,"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."}}