{"id":"W6939045037","doi":"10.6068/dp14ba8db0a6b13","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: 15 years and over, Employment, No degree, certificate or diploma, Males, Immigrants, landed 5 or less years earlier | 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":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Unemployment; Official statistics; Descriptive statistics; Census; Socioeconomic status; 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":[0.002714966,0.002529494,0.002980728,0.008005122,0.003433792,0.004768598,0.00560211,0.001427467,0.0851602],"category_scores_gemma":[0.01822382,0.001934518,0.002519306,0.03729443,0.0006089804,0.002301097,0.002425767,0.003334047,0.04551655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05589882,"about_ca_system_score_gemma":0.1504492,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9958216,"about_ca_topic_score_gemma":0.9944659,"domain_scores_codex":[0.9952319,0.0003421502,0.0005315057,0.0005576963,0.002190062,0.001146604],"domain_scores_gemma":[0.9634873,0.001137403,0.001075283,0.0009519149,0.03151382,0.001834279],"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":[0.00003604255,0.000009662691,0.001522327,0.0002751119,0.00002840935,0.000007801866,0.00002905107,0.0001088844,0.00001185886,0.0003314115,0.9955515,0.002087876],"study_design_scores_gemma":[0.0002506345,0.00002185853,0.04590964,0.001252075,0.0001155313,0.00003686277,0.0006998263,0.0005847277,0.0002352272,0.0007709411,0.9500015,0.0001211282],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008432336,0.00006323827,0.00003040022,0.0001515725,0.00004156132,0.00002401745,0.9985384,0.000061707,0.001004821],"genre_scores_gemma":[0.001140097,0.0003518306,0.0005273325,0.0002425559,0.00002715709,0.0001962463,0.9911243,0.0001367547,0.006253747],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0851602,"threshold_uncertainty_score":0.4055762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04802927193679164,"score_gpt":0.2694962250590895,"score_spread":0.2214669531222979,"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."}}