{"id":"W2914246186","doi":"10.2298/zmsdn1867627p","title":"Attracting and retaining highly educated individuals: Two examples of immigration policies","year":2018,"lang":"en","type":"article","venue":"Zbornik Matice srpske za drustvene nauke","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Immigration policy; Human capital; Population; Political science; Economic growth; Development economics; Business; Demographic economics; Economics; Sociology; Law","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":[0.002551228,0.0003612525,0.0001668904,0.00147441,0.01257657,0.003966145,0.001155784,0.00315638,0.002157116],"category_scores_gemma":[0.005248052,0.0001634778,0.0002936955,0.002554354,0.006929408,0.001278803,0.002848073,0.002184076,0.0002533964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01234696,"about_ca_system_score_gemma":0.02382726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3746742,"about_ca_topic_score_gemma":0.5592338,"domain_scores_codex":[0.996042,0.001441217,0.000105928,0.0002107326,0.001012586,0.001187496],"domain_scores_gemma":[0.9974177,0.0009933466,0.0003775431,0.0001983371,0.0006103936,0.0004027078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00003664592,0.000155148,0.01392801,0.0002327736,0.00001277286,0.00127553,0.08819098,0.001501947,0.0006819456,0.7942599,0.02245651,0.0772678],"study_design_scores_gemma":[0.00005545544,0.0001149013,0.04120854,0.0009481836,0.00004711099,0.001270938,0.09723503,0.00324636,0.002174114,0.04861604,0.8049684,0.0001150864],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3921099,0.004198411,0.01515522,0.04195599,0.0004498611,0.0003953616,0.0003108537,0.0001438487,0.5452805],"genre_scores_gemma":[0.8872797,0.005507472,0.0199411,0.004793352,0.0000999313,0.0003116072,0.0001670889,0.00006444424,0.08183531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3746742,"threshold_uncertainty_score":0.7449868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03206961971388345,"score_gpt":0.3446962360387512,"score_spread":0.3126266163248677,"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."}}