{"id":"W6957587921","doi":"10.6068/dp14ba8eba32168","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, educational attainment, sex and age group | Variable: 25 to 54 years, Unemployment rate, High school graduate, Females, Immigrants, landed more than 5 to 10 years earlier | Units: , 2006-2013. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-092.","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; Diversity (politics); Unemployment; Population statistics","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":[0.002538177,0.002368172,0.002864833,0.007460859,0.003351785,0.004607251,0.005250775,0.001342108,0.08337688],"category_scores_gemma":[0.01752876,0.001975019,0.002342237,0.03476631,0.0006042519,0.002328319,0.002237514,0.003305398,0.04171066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05556524,"about_ca_system_score_gemma":0.1520397,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996009,"about_ca_topic_score_gemma":0.9943719,"domain_scores_codex":[0.9956449,0.0003067509,0.0005110125,0.0005168814,0.001980242,0.001040267],"domain_scores_gemma":[0.9649919,0.001067727,0.001032927,0.0008415175,0.03028573,0.001780186],"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":[0.00003978107,0.00001025241,0.001690732,0.0003083163,0.00002828181,0.000008108045,0.00003187597,0.0001055639,0.00001267023,0.0003215937,0.9950235,0.002419277],"study_design_scores_gemma":[0.0002924535,0.00002567164,0.05636166,0.001457926,0.0001309799,0.00004329106,0.0007791039,0.000590783,0.0002376667,0.0007425465,0.9392163,0.0001216168],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001023572,0.00007739412,0.00003462411,0.0001781157,0.00005047094,0.00003112785,0.9982361,0.00007016043,0.001219656],"genre_scores_gemma":[0.001475726,0.0005047677,0.0006565659,0.0003034664,0.00003240446,0.0002426115,0.9890125,0.0001604855,0.007611491],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08337688,"threshold_uncertainty_score":0.4031559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03150135248422143,"score_gpt":0.2674334910183567,"score_spread":0.2359321385341352,"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."}}