{"id":"W6976749889","doi":"10.6068/dp14ba8d3c84f54","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, country of birth, sex and age group | Variable: 15 years and over, North America, Employment rate, Females, Immigrants, landed more than 5 to 10 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; Census; Descriptive statistics; 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":[0.002682733,0.002597508,0.003041854,0.007799326,0.003300637,0.004824872,0.005822052,0.001456469,0.08764422],"category_scores_gemma":[0.0190014,0.001978785,0.002577287,0.03802253,0.00060215,0.002348181,0.00248578,0.003347423,0.04961256],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05203539,"about_ca_system_score_gemma":0.1403502,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9949089,"about_ca_topic_score_gemma":0.9931747,"domain_scores_codex":[0.9952814,0.0003575963,0.0005423704,0.0005566477,0.002144339,0.001117645],"domain_scores_gemma":[0.962814,0.001220926,0.001114325,0.001018928,0.03200918,0.001822647],"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":[0.00003311447,0.000008728374,0.001352434,0.000258825,0.00002762609,0.000007111829,0.00002535362,0.000100554,0.00001025152,0.0003144445,0.9960284,0.001833173],"study_design_scores_gemma":[0.0002557864,0.00002041305,0.04047185,0.001281609,0.0001127277,0.00003605074,0.0006477757,0.0005470173,0.0002208081,0.000791627,0.9554954,0.0001188929],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006999887,0.00005547537,0.00002648335,0.0001378493,0.00003721046,0.00002141899,0.9987092,0.00005699488,0.0008855141],"genre_scores_gemma":[0.0009641913,0.0003116595,0.0004743086,0.0002257561,0.00002566045,0.0001917413,0.9923294,0.0001331596,0.005344059],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08764422,"threshold_uncertainty_score":0.3775449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01688814649990841,"score_gpt":0.2384745682643183,"score_spread":0.2215864217644098,"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."}}