{"id":"W4256214840","doi":"10.32920/ryerson.14663247.v1","title":"The enhanced mentoring program for skilled Korean immigrants: an effective tool for successful integration into the Canadian labour market? (A Grant Proposal)","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Immigration; Settlement (finance); Human capital; Multiculturalism; Ethnic group; Business; Service (business); The Internet; Political science; Labour economics; Demographic economics; Economic growth; Economics; Marketing; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.003212896,0.00029698,0.0001623245,0.0005676132,0.002817466,0.00114835,0.00151822,0.002204221,0.04361222],"category_scores_gemma":[0.006102124,0.0001597557,0.0003289591,0.0004287887,0.000745105,0.0005811725,0.002800978,0.0008522999,0.00395155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002745056,"about_ca_system_score_gemma":0.03760679,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1347356,"about_ca_topic_score_gemma":0.279094,"domain_scores_codex":[0.9988831,0.0002642349,0.00004410215,0.00006134444,0.0003120285,0.0004352842],"domain_scores_gemma":[0.9927423,0.0005308551,0.0001328461,0.0001719953,0.001302608,0.005119289],"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":[0.001087142,0.005877154,0.009496615,0.0005535695,0.00002591683,0.001313367,0.001414373,0.0004001375,0.004982226,0.00376794,0.513812,0.4572695],"study_design_scores_gemma":[0.004040326,0.007382751,0.1827236,0.0009737102,0.0001472202,0.001929766,0.01005438,0.003464254,0.005964752,0.002380897,0.7807305,0.0002077461],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"protocol","genre_scores_codex":[0.3970353,0.003206663,0.007970811,0.1777819,0.01333898,0.04903657,0.007420821,0.001810483,0.3423986],"genre_scores_gemma":[0.5311065,0.004998398,0.03790653,0.01520979,0.003205455,0.01462235,0.005337814,0.0002130036,0.3874001],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.8652644,"threshold_uncertainty_score":0.2679027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01101673863001232,"score_gpt":0.3067807384934132,"score_spread":0.2957639998634009,"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."}}