{"id":"W4408438920","doi":"10.1162/asep_a_00937","title":"Quest for Talents: Attraction and Retention of  Highly Skilled Overseas Chinese in the United States and Canada","year":2025,"lang":"en","type":"article","venue":"Asian Economic Papers","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Attraction; Business; Linguistics; Philosophy","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":[0.0003444745,0.0001477184,0.0001955225,0.0009038359,0.002869186,0.001223631,0.000671495,0.0002609262,0.002600078],"category_scores_gemma":[0.001107609,0.0001018818,0.0001986295,0.00183213,0.000680806,0.0003449699,0.0008776414,0.0005808159,0.000231747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007291686,"about_ca_system_score_gemma":0.01693,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9852442,"about_ca_topic_score_gemma":0.9935615,"domain_scores_codex":[0.999716,0.0000223784,0.000009776434,0.00002712811,0.00007179714,0.0001530196],"domain_scores_gemma":[0.9987705,0.00005970611,0.0001533696,0.00002174356,0.0004107055,0.0005840471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003857175,0.00006188733,0.9872419,0.00001328534,0.00001535894,0.0001014359,0.004398005,0.00008750481,0.0001346719,0.0001819074,0.001027664,0.006697796],"study_design_scores_gemma":[0.000002466656,0.0000205448,0.9803743,0.00001193826,0.000005756128,0.0000229593,0.01829326,0.0002230344,0.00005770279,0.00002855711,0.0009514666,0.000008064732],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985898,0.000041204,0.000012268,0.0001326631,0.000002440101,0.000006914254,0.0002873655,0.000001239227,0.0009261578],"genre_scores_gemma":[0.9978649,0.0001028291,0.00002246077,0.00004751482,0.000001539652,0.000003844322,0.0002416009,0.000001156225,0.001714092],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01475585,"threshold_uncertainty_score":0.05290514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005033359477937061,"score_gpt":0.257002118736129,"score_spread":0.251968759258192,"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."}}