{"id":"W2268583882","doi":"10.1080/1070289x.2015.1091317","title":"Culturally tailored workers for specialised destinations: producing Filipino migrant subjects for export","year":2015,"lang":"en","type":"article","venue":"Identities","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"University of British Columbia Graduate School","keywords":"Destinations; Workforce; Scholarship; Migrant workers; State (computer science); Ideal (ethics); Political science; Business; Sociology; Demographic economics; Economic growth; Economics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002694819,0.0006596498,0.0003925689,0.000986354,0.006115099,0.004010672,0.001124409,0.0008901305,0.008776511],"category_scores_gemma":[0.003454676,0.0003432807,0.0002272927,0.0008272188,0.001705433,0.001395669,0.003119003,0.0008912715,0.001259075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001545433,"about_ca_system_score_gemma":0.004077859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0198612,"about_ca_topic_score_gemma":0.06598353,"domain_scores_codex":[0.999193,0.0004150538,0.00001942344,0.0000777042,0.00007081028,0.0002240387],"domain_scores_gemma":[0.9990401,0.0003373339,0.0001066807,0.00008997008,0.0001693399,0.0002565107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002244085,0.001315583,0.05420337,0.0003251003,0.0000108304,0.002077738,0.8680714,0.00005805001,0.005206185,0.001314258,0.001822499,0.06537057],"study_design_scores_gemma":[0.00002578781,0.0006333702,0.0318519,0.0001695837,0.00001463304,0.0002113748,0.9526104,0.00007914236,0.0008720721,0.0002517606,0.01325844,0.00002155772],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962239,0.00009871653,0.0002851831,0.0002078293,0.0000113921,0.0002228912,0.00003777144,0.000005366528,0.002907038],"genre_scores_gemma":[0.9831778,0.0005327779,0.004351543,0.0004787343,0.00002011589,0.000596268,0.00009166269,0.0000196461,0.01073141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0198612,"threshold_uncertainty_score":0.03949118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05825627803125124,"score_gpt":0.3276263017723761,"score_spread":0.2693700237411249,"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."}}