{"id":"W2163224528","doi":"10.1111/tran.12072","title":"Policy mobilities in the race for talent: competitive state strategies in international student mobility","year":2014,"lang":"en","type":"article","venue":"Transactions of the Institute of British Geographers","topic":"Higher Education Governance and Development","field":"Social Sciences","cited_by":92,"is_retracted":false,"has_abstract":true,"ca_institutions":"Association of Universities and Colleges of Canada","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Mobilities; Globalization; State (computer science); Higher education; Immigration; Race (biology); Political science; Sociology; International education; Economic growth; Economics; Social science; Market economy; Gender studies","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007304319,0.00006169736,0.0001308532,0.00009165966,0.0001352957,0.00004738788,0.0004904174,0.0000327624,0.00002516044],"category_scores_gemma":[0.00004774987,0.00005842534,0.000110343,0.0004801234,0.0007470184,0.0003624771,0.000007123155,0.00009228096,3.661698e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008492604,"about_ca_system_score_gemma":0.0003975818,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.06769202,"about_ca_topic_score_gemma":0.1826718,"domain_scores_codex":[0.9989398,0.0001190606,0.0003058113,0.0001312544,0.0003536047,0.0001504775],"domain_scores_gemma":[0.9994692,0.0001283965,0.0001149341,0.0001423996,0.0001241249,0.00002097769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002331042,0.005137019,0.1492361,0.0003304482,0.000369819,0.000002768404,0.4302786,0.09142932,0.0001588595,0.2346674,0.0006999,0.08745667],"study_design_scores_gemma":[0.0009897982,0.00004993482,0.8408926,0.0002261522,0.00001415711,0.000001557655,0.1090324,0.00002289773,0.00007150813,0.01688983,0.03165769,0.0001514768],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9860829,0.00006667787,0.002261094,0.002612384,0.0007699534,0.000647225,0.0001201233,0.000009660963,0.007429949],"genre_scores_gemma":[0.9985948,0.0003336484,0.0005155059,0.00008210288,0.00002980605,0.0001298812,0.000002777304,0.000003167255,0.0003083355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6916565,"threshold_uncertainty_score":0.9385163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00982396505424078,"score_gpt":0.3060463653521964,"score_spread":0.2962224002979556,"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."}}