{"id":"W2030610505","doi":"10.1068/a37246","title":"The Migration–Immigration Link in Canada's Gateway Cities: A Comparative Study of Toronto, Montreal, and Vancouver","year":2006,"lang":"en","type":"article","venue":"Environment and Planning A Economy and Space","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Statistics Canada","funders":"","keywords":"Immigration; Microdata (statistics); Net migration rate; Metropolitan area; Demographic economics; Geography; Internal migration; Population; Restructuring; Gateway (web page); Demography; Economic geography; Political science; Population growth; Census; Sociology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004053655,0.0003529649,0.0003781815,0.002230944,0.005674256,0.002065189,0.0008236294,0.0003507198,0.002319487],"category_scores_gemma":[0.001789507,0.0003230556,0.0003033006,0.006417215,0.001508056,0.0005056257,0.00156434,0.0005300453,0.0001886767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0331024,"about_ca_system_score_gemma":0.02655956,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9964488,"about_ca_topic_score_gemma":0.9993744,"domain_scores_codex":[0.999341,0.00006161682,0.00002146285,0.00007258048,0.0001588606,0.0003445923],"domain_scores_gemma":[0.9987391,0.0001064156,0.0001873705,0.000046713,0.0004354822,0.0004848819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001047049,0.00007344959,0.9544007,0.00007841571,0.00006171317,0.0007727721,0.0269098,0.0002240901,0.0005513944,0.001338541,0.002137247,0.01334713],"study_design_scores_gemma":[0.000006258559,0.0000214421,0.9702294,0.00003900528,0.00001749668,0.0001001077,0.02732637,0.0001680973,0.00007123039,0.00004133234,0.001964699,0.00001463975],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974025,0.0002380942,0.00002980965,0.0001216496,0.000004507439,0.00001699781,0.0003440003,0.000003096845,0.00183924],"genre_scores_gemma":[0.9976833,0.0003787576,0.00009052943,0.00004100509,0.000002610336,0.00001485753,0.0004528924,0.000004125634,0.001331942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0331024,"threshold_uncertainty_score":0.2401759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008060149137175033,"score_gpt":0.2150998047919233,"score_spread":0.2070396556547482,"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."}}