{"id":"W3123151084","doi":"","title":"Ethnic Inequality in Canada: Economic and Health Dimensions","year":2007,"lang":"en","type":"article","venue":"Social and Economic Dimensions of an Aging Population Research Papers","topic":"Employment and Welfare Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Ethnic group; Disadvantaged; Immigration; Inequality; Census; Demographic economics; Context (archaeology); Population; Social inequality; Socioeconomic status; Geography; Political science; Gender studies; Demography; Sociology; Economic growth; 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":["sts"],"consensus_categories":[],"category_scores_codex":[0.003839993,0.000115519,0.000349209,0.0002193818,0.001308673,0.000005944816,0.00007142743,0.00007813261,0.00006187369],"category_scores_gemma":[0.00004979723,0.0001046566,0.00002523782,0.00009261011,0.0001277934,0.0001366741,0.0001848312,0.0004028103,0.000004530995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001295486,"about_ca_system_score_gemma":0.0008657621,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9485586,"about_ca_topic_score_gemma":0.988677,"domain_scores_codex":[0.9978627,0.0004222459,0.0006659792,0.000302626,0.000132536,0.0006139031],"domain_scores_gemma":[0.9989655,0.0004755859,0.0001743859,0.0001369401,0.00003765948,0.000209951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003590457,0.00001751567,0.9775057,0.00006506839,0.00002224764,0.000001405412,0.004388787,0.00004418161,0.00004149694,0.006417595,0.0009080162,0.01055208],"study_design_scores_gemma":[0.0004931249,0.00004100972,0.9813898,0.00006055663,0.000003167566,2.425704e-7,0.01575707,0.0001337774,0.000002773118,0.001100725,0.0009132304,0.0001045063],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910838,0.0002451852,3.675645e-7,0.006852509,0.000212789,0.0004064739,0.00003063551,0.00001640904,0.001151842],"genre_scores_gemma":[0.9988235,0.0004259288,0.000042149,0.0003766792,0.00009584331,0.00001395567,0.00003785265,0.00001386932,0.0001701788],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04011844,"threshold_uncertainty_score":0.9999915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2204325303163736,"score_gpt":0.5001981081757177,"score_spread":0.2797655778593442,"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."}}