{"id":"W2997118103","doi":"10.1007/978-3-030-22874-3_4","title":"The Canadian Census and Mixed Race: Tracking Mixed Race Through Ancestry, Visible Minority Status, and Métis Population Groups in Canada","year":2020,"lang":"en","type":"book-chapter","venue":"","topic":"Canadian Identity and History","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centennial College","funders":"","keywords":"Census; Ethnic group; Geography; Race (biology); Population; American Community Survey; Indigenous; Mixed race; Demography; Tracking (education); Comparability; Genealogy; Gender studies; Political science; Sociology; History; 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":[0.001258117,0.000476477,0.0004810314,0.004201107,0.005583477,0.003039141,0.001570039,0.0005602874,0.005569853],"category_scores_gemma":[0.004779983,0.0005832118,0.0005330601,0.01477597,0.001022168,0.001432786,0.001321933,0.0009907184,0.001030542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06051533,"about_ca_system_score_gemma":0.1855841,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.999405,"about_ca_topic_score_gemma":0.9997738,"domain_scores_codex":[0.9989347,0.00008498813,0.00004002337,0.00008620276,0.0006023358,0.0002517776],"domain_scores_gemma":[0.9979271,0.0001799785,0.00007899478,0.00005409669,0.00146449,0.0002952927],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00003600169,0.00002305448,0.09588464,0.0003454394,0.00005186666,0.0001068023,0.007575943,0.001317278,0.0001586934,0.02276118,0.6049399,0.2667992],"study_design_scores_gemma":[0.00001259456,0.00001726007,0.4757905,0.00115565,0.00009793496,0.0001292807,0.02216481,0.002891862,0.0003710666,0.005284598,0.4919654,0.000119026],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1419124,0.1017514,0.01042227,0.06145653,0.004334198,0.0005984195,0.2370964,0.00115368,0.4412747],"genre_scores_gemma":[0.5758801,0.09193201,0.02509782,0.004525597,0.0004496716,0.0004850619,0.0528442,0.0006448384,0.2481407],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06051533,"threshold_uncertainty_score":0.4390715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02977119690054296,"score_gpt":0.2445529595648207,"score_spread":0.2147817626642777,"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."}}