{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00123545,0.0005614675,0.0008173831,0.0001091335,0.0006605315,0.0003444219,0.0009382657,0.0003523676,0.001546191],"category_scores_gemma":[0.0001561422,0.0004874303,3.512316e-7,0.0005259973,0.000429472,0.0003706428,0.0008272934,0.0003729994,0.000008731815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002617244,"about_ca_system_score_gemma":0.004304697,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9999567,"about_ca_topic_score_gemma":0.9999604,"domain_scores_codex":[0.9956872,0.0007829823,0.0005873716,0.001081938,0.001072401,0.0007881242],"domain_scores_gemma":[0.9966872,0.0008817842,0.0004802466,0.0009546282,0.0001118983,0.0008842633],"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":[0.000172844,0.00006763415,0.00621418,0.0002413414,0.0003547659,0.00008909917,0.00005627544,0.000002428994,0.000002904528,0.0001615436,0.9925604,0.0000765105],"study_design_scores_gemma":[0.0005980189,0.00005407576,0.006663329,0.00003618182,0.0003641449,0.00001030275,0.0004650466,0.0002893287,1.082997e-8,9.608237e-7,0.9908541,0.0006644433],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001083493,0.003976752,0.000004648989,0.00003067478,0.0002625714,0.0005759071,0.9948265,0.00003549279,0.000179119],"genre_scores_gemma":[0.0003189521,0.00416308,0.0001038027,0.0002352655,0.0001188006,0.00001457067,0.9640343,0.00007777526,0.03093345],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03079219,"threshold_uncertainty_score":0.9997577,"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."}}