{"id":"W7132977511","doi":"","title":"Turning Brain Drain into Brain Gain: Harnessing Pakistan&apos;s Skilled Diaspora","year":2021,"lang":"","type":"dissertation","venue":"TSpace","topic":"Diaspora, migration, transnational identity","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diaspora; Knowledge transfer; Exploratory research; Interview; Reciprocity (cultural anthropology); Developing country; Emigration; Brain drain","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":[0.002349561,0.0003556137,0.0002050503,0.0007098463,0.007794645,0.005852432,0.0005492849,0.0006566716,0.003355841],"category_scores_gemma":[0.003904002,0.000213994,0.0001911417,0.0006741629,0.007046839,0.003629927,0.007265326,0.001599067,0.0003490348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002885778,"about_ca_system_score_gemma":0.005629018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009326154,"about_ca_topic_score_gemma":0.02801308,"domain_scores_codex":[0.9980832,0.00113515,0.00004057154,0.00008814295,0.0001585702,0.0004942809],"domain_scores_gemma":[0.9978052,0.0009167854,0.0003111364,0.0001416523,0.0001889451,0.0006363843],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005347363,0.00009701365,0.02978335,0.0002258944,0.00001554323,0.002647493,0.9087363,0.00008807369,0.00149485,0.01222575,0.002848749,0.04178348],"study_design_scores_gemma":[0.000004176643,0.00006397088,0.007613332,0.0001753512,0.000007124414,0.0003118294,0.9688239,0.00007839879,0.0003680912,0.00150959,0.021034,0.00001025418],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.9672226,0.0004962147,0.001439127,0.003615893,0.00006410007,0.00008826453,0.00005621972,0.00001080223,0.02700669],"genre_scores_gemma":[0.997368,0.0005775756,0.0004671822,0.0003910146,0.0000089846,0.00003043347,0.00001212788,0.000003197832,0.00114149],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.009326154,"threshold_uncertainty_score":0.02093786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.029737928819044,"score_gpt":0.41545513666892,"score_spread":0.385717207849876,"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."}}