{"id":"W2936728258","doi":"10.1007/s42650-019-00002-x","title":"Literacy Skills of the Future Canadian Working-Age Population: Assessing the Skill Gap Between the Foreign- and Canadian-Born","year":2019,"lang":"en","type":"article","venue":"Canadian Studies in Population","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Immigration; Literacy; Socioeconomic status; Population; Adult literacy; Foreign born; Demographic economics; Microsimulation; Geography; Psychology; Demography; Economic growth; Sociology; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007197497,0.0003570455,0.0002662458,0.00177232,0.002224565,0.001513806,0.001042881,0.0005532596,0.002800783],"category_scores_gemma":[0.003266288,0.0001850799,0.0004951349,0.00158257,0.0005845566,0.0006825448,0.001105587,0.0007703386,0.000398137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008079784,"about_ca_system_score_gemma":0.01359087,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9805461,"about_ca_topic_score_gemma":0.989749,"domain_scores_codex":[0.9996069,0.00001859311,0.00001976759,0.00003866528,0.0001416311,0.0001743932],"domain_scores_gemma":[0.9988462,0.00006821946,0.0001450358,0.00002527748,0.0005297068,0.0003854894],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007335238,0.0001342106,0.9801641,0.00003394243,0.00003104543,0.0001464406,0.006426684,0.0001006304,0.0002160322,0.0002802404,0.001528745,0.01086456],"study_design_scores_gemma":[0.000003747399,0.00004565192,0.9913658,0.00002239774,0.00001508958,0.00006173459,0.00697465,0.0002086665,0.0000681819,0.00004411602,0.001179193,0.00001080092],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952347,0.0001845975,0.00004028603,0.0001537482,0.00001120646,0.00002223385,0.00118504,0.000003782626,0.00316447],"genre_scores_gemma":[0.9974138,0.0001819231,0.0001055207,0.00005864476,0.000003300727,0.00001464555,0.0008503401,0.0000028185,0.001368992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01945394,"threshold_uncertainty_score":0.05862319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03723230328178388,"score_gpt":0.3364880963173195,"score_spread":0.2992557930355356,"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."}}