{"id":"W6957858416","doi":"10.6068/dp14ba8b080961","title":"Trend 2006 - 2013. Statistics Canada. CANSIM: Ethnic Diversity and Immigration - Labor Market and Income | Country: Canada | Table: Labour force survey estimates (LFS), by immigrant status, educational attainment, sex and age group | Variable: 25 to 54 years, Unemployment, No degree, certificate or diploma, Females, Landed immigrants | Units: , 2006-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-094.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"Legal and Regulatory Analysis","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Unemployment; Official statistics; Descriptive statistics; Socioeconomic status; Census; Population; Ethnic group; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002693315,0.00255872,0.002884828,0.007859532,0.00332116,0.004890364,0.005516484,0.001465832,0.09724986],"category_scores_gemma":[0.01909347,0.001961632,0.002394943,0.03764377,0.0005956781,0.002402533,0.002534775,0.003245615,0.05445255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04892878,"about_ca_system_score_gemma":0.1330193,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9941686,"about_ca_topic_score_gemma":0.992108,"domain_scores_codex":[0.995415,0.0003459807,0.0005207146,0.0005508304,0.002058392,0.001109111],"domain_scores_gemma":[0.9661167,0.001252242,0.001072764,0.00103899,0.02872868,0.001790456],"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":[0.00002936291,0.000008052659,0.00113013,0.0002364688,0.00002250677,0.000006510641,0.00002412035,0.00009422924,0.000009751926,0.0003061223,0.9963838,0.001748939],"study_design_scores_gemma":[0.0002316913,0.0000184336,0.03359007,0.001155261,0.00009166037,0.00003270465,0.0005695033,0.0005191795,0.0002103641,0.0007666143,0.9627084,0.000106047],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005937664,0.00004504777,0.0000251842,0.0001179054,0.00003363654,0.00001986688,0.9987913,0.00005667347,0.0008510168],"genre_scores_gemma":[0.000767138,0.0002519418,0.0004122387,0.000182905,0.00002131326,0.0001695144,0.9932221,0.0001260426,0.004846748],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09724986,"threshold_uncertainty_score":0.3550048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04868588843855674,"score_gpt":0.2808614367588553,"score_spread":0.2321755483202986,"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."}}