{"id":"W6958040157","doi":"10.6068/dp14ba88e19bb61","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: 25 to 54 years, Total population, Employment rate, Both sexes, Total population | 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; Population; Descriptive statistics; Socioeconomic status; Ethnic group; Summary statistics; 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":[0.002791417,0.0025409,0.002932222,0.007591993,0.003368099,0.004627049,0.005795478,0.001422849,0.09446653],"category_scores_gemma":[0.01900591,0.002001917,0.002516196,0.03542836,0.0005889376,0.002367732,0.002531541,0.00335301,0.04884643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05060005,"about_ca_system_score_gemma":0.1368414,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9944413,"about_ca_topic_score_gemma":0.9927042,"domain_scores_codex":[0.9954337,0.00035601,0.0005358724,0.0005270616,0.002065948,0.001081341],"domain_scores_gemma":[0.9646338,0.001257651,0.001096098,0.001030894,0.0301177,0.00186388],"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":[0.00003224672,0.000008518933,0.001375137,0.0002757413,0.00002643618,0.000007210136,0.00002767689,0.00009731993,0.00001097397,0.0003238706,0.9958604,0.001954575],"study_design_scores_gemma":[0.0002844072,0.00002180722,0.04378626,0.001475053,0.0001115424,0.00003912003,0.0006672513,0.0005758911,0.0002366582,0.0008713523,0.9518076,0.0001231312],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007024034,0.00005142987,0.00002933825,0.0001334576,0.00003637816,0.00002510039,0.9986843,0.00005693783,0.0009128168],"genre_scores_gemma":[0.0009515913,0.000313396,0.0005303692,0.0002254731,0.0000244792,0.0002288526,0.9923057,0.0001369227,0.005283095],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09446653,"threshold_uncertainty_score":0.3671308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01505231849248987,"score_gpt":0.2372784713130937,"score_spread":0.2222261528206039,"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."}}