{"id":"W6939353942","doi":"10.6068/dp14ba8e00f7846","title":"Trend 2006 - 2013. Statistics Canada. CANSIM: Ethnic Diversity and Immigration - Immigrants and Nonpermanent Residents | 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, Unemployment rate, Males, Immigrants, landed more than 10 years earlier | Units: , 2006-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-092.","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; Census; Socioeconomic status; Population; Official statistics; Ethnic group; Population statistics; Diversity (politics); Unemployment; American Community Survey","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":[0.002572187,0.002355787,0.00282462,0.007442957,0.003338846,0.004640685,0.005306418,0.00133041,0.08493317],"category_scores_gemma":[0.01827204,0.001921849,0.002294594,0.03501642,0.0005928811,0.002343898,0.002320687,0.003312492,0.04410571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05369322,"about_ca_system_score_gemma":0.1471035,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9953158,"about_ca_topic_score_gemma":0.9935109,"domain_scores_codex":[0.9955199,0.0003261818,0.000516343,0.0005287284,0.002050291,0.001058622],"domain_scores_gemma":[0.965188,0.001101854,0.001041627,0.000857619,0.02999818,0.001812702],"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":[0.00003621285,0.000009522149,0.001547701,0.0002772895,0.00002657215,0.000007715993,0.00003089268,0.0001003702,0.00001125954,0.000320883,0.9954097,0.002221967],"study_design_scores_gemma":[0.0002652725,0.00002308712,0.05025709,0.001383603,0.0001211447,0.00004094997,0.0007887919,0.0005579006,0.0002250164,0.0007859558,0.9454345,0.0001167413],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009489018,0.00007063977,0.00003340177,0.0001754076,0.00004672611,0.00002912476,0.9983157,0.00006549249,0.001168566],"genre_scores_gemma":[0.001334831,0.0004641596,0.0006214584,0.000287382,0.00003178011,0.000246007,0.9896054,0.0001532675,0.007255679],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08493317,"threshold_uncertainty_score":0.3895734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01738239216816325,"score_gpt":0.2380865450474164,"score_spread":0.2207041528792532,"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."}}