{"id":"W4389572618","doi":"10.1080/15562948.2023.2289116","title":"Rethinking Migration Studies for 2050","year":2023,"lang":"en","type":"article","venue":"Journal of Immigrant & Refugee Studies","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada; Narodowe Centrum Nauki; Narodowym Centrum Nauki; European Commission","keywords":"Urbanization; Citizenship; Globalization; Poverty; Population; Economic geography; Unemployment; Corporate governance; Development economics; Sociology; Political science; Social transformation; Identity change; Political economy; Social change; Net migration rate; Economic growth; Economics; Population growth; Social science; Politics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.01958585,0.0006767758,0.0008987663,0.006390261,0.009807942,0.01016705,0.002282036,0.004455119,0.007161232],"category_scores_gemma":[0.01765104,0.0002953995,0.0008503753,0.005501919,0.01808947,0.02129039,0.00898652,0.008277041,0.0007571003],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01160188,"about_ca_system_score_gemma":0.01272658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03163537,"about_ca_topic_score_gemma":0.08964303,"domain_scores_codex":[0.9927853,0.004950623,0.0003934086,0.0005688298,0.0005502152,0.0007516837],"domain_scores_gemma":[0.9902701,0.005772322,0.0007427408,0.0008845742,0.001416807,0.0009133689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000505207,0.00005065975,0.002894973,0.0008119261,0.0000544581,0.0002702187,0.0963413,0.0001335963,0.0002541462,0.7545936,0.07383482,0.07070982],"study_design_scores_gemma":[0.000007306351,0.00004593778,0.006312152,0.003275965,0.00002498754,0.0002021224,0.07164023,0.00007766086,0.000127118,0.06932855,0.8489258,0.00003219737],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.0586706,0.2356152,0.004844119,0.5852957,0.02689004,0.00007800976,0.0006745605,0.00006695987,0.08786486],"genre_scores_gemma":[0.628774,0.1312638,0.00956833,0.1795121,0.01280828,0.0004698974,0.0007475728,0.0002579365,0.03659797],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03163537,"threshold_uncertainty_score":0.1035811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08726805960270911,"score_gpt":0.4075718353486255,"score_spread":0.3203037757459164,"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."}}