{"id":"W6976813191","doi":"10.6068/dp14ba8ab994576","title":"Trend 2006 - 2013. Statistics Canada. CANSIM: Ethnic Diversity and Immigration - Education, Training and Skills | Country: Canada | Table: Labour force survey estimates (LFS), by immigrant status, educational attainment, sex and age group | Variable: 25 to 54 years, Not in labour force, High school graduate, Females, Born in Canada | Units: , 2006-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-089.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Educational Theory and Curriculum Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Census; Socioeconomic status; Ethnic group; Population; Statistics education; Official statistics; Population statistics; Diversity (politics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001294074,0.0004422758,0.0006316336,0.0001122391,0.0004716513,0.0001773851,0.0006777376,0.0001893834,0.0004654213],"category_scores_gemma":[0.0004156825,0.0004734252,1.822218e-7,0.000485182,0.0002329847,0.0003422225,0.0004589823,0.0004466304,0.000001984867],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008517018,"about_ca_system_score_gemma":0.02803645,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999983,"about_ca_topic_score_gemma":0.9999989,"domain_scores_codex":[0.996356,0.0006331664,0.0005601469,0.0008543578,0.0008795375,0.0007168259],"domain_scores_gemma":[0.9970255,0.001290693,0.0003788407,0.0005492822,0.0001157039,0.000639925],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002575504,0.00007670982,0.009148309,0.0001489537,0.00008369659,0.00002250431,0.0002127021,0.00001058027,4.209111e-7,0.003112451,0.987042,0.0001159854],"study_design_scores_gemma":[0.000378811,0.00002417637,0.02312536,0.00005735905,0.00007058051,0.000007483578,0.007237653,0.00003130149,4.691162e-9,0.00001328779,0.968518,0.0005359848],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0008168654,0.003904537,0.000002011921,0.00005663186,0.0005131302,0.000610153,0.9939141,0.00001228707,0.0001703081],"genre_scores_gemma":[0.003217145,0.00373189,0.0001325668,0.0005605326,0.0001323507,0.00003656571,0.9860774,0.00005302513,0.006058556],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02718475,"threshold_uncertainty_score":0.9997718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03305684129398526,"score_gpt":0.2820534170232802,"score_spread":0.248996575729295,"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."}}