{"id":"W4391659142","doi":"10.32920/25193495","title":"International Education and Brain Drain: A Case Study of Nigerians in Canada","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Toronto Metropolitan University","funders":"","keywords":"Nigerians; Government (linguistics); Language change; Corporate governance; Political science; Brain drain; Economic growth; Business; Economics; 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":[0.000649515,0.0004620575,0.0004378648,0.001384058,0.03093977,0.003527545,0.001202504,0.001773505,0.003266164],"category_scores_gemma":[0.001916871,0.0003159447,0.0002532585,0.003207928,0.004596845,0.0009715275,0.003591163,0.002998775,0.0001850695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03488033,"about_ca_system_score_gemma":0.05622611,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9589984,"about_ca_topic_score_gemma":0.9885528,"domain_scores_codex":[0.9987809,0.0001973554,0.0000262987,0.00006281893,0.0001661974,0.0007664139],"domain_scores_gemma":[0.9983829,0.0002530734,0.0001376509,0.00002792445,0.000295097,0.0009033044],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008094319,0.0003870229,0.09058594,0.0002308902,0.00001851557,0.03942005,0.8315197,0.0003150735,0.0009791367,0.007041378,0.005082018,0.02433928],"study_design_scores_gemma":[0.000003256655,0.00003434009,0.01959269,0.0001210905,0.000007963948,0.001217072,0.9654782,0.0001198377,0.0001296884,0.0001607905,0.01311607,0.00001898669],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881324,0.0004592482,0.00007888579,0.002069106,0.00003259521,0.00006275035,0.00005369088,0.000003005277,0.009108298],"genre_scores_gemma":[0.9906222,0.001571141,0.0002135697,0.0006066525,0.00001194792,0.00002429472,0.00003792974,0.000006969415,0.00690526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04100162,"threshold_uncertainty_score":0.2530757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01667907359789269,"score_gpt":0.3332811661897459,"score_spread":0.3166020925918532,"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."}}