{"id":"W4229019170","doi":"10.1111/imig.13021","title":"Migration 2030: Governing migration in a globalising world","year":2022,"lang":"en","type":"article","venue":"International Migration","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Excellence; Human migration; Political science; Pandemic; China; Corporate governance; Inequality; Coronavirus disease 2019 (COVID-19); Development economics; Political economy; Sociology; Economic growth; Population; Economics; Law; Management","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":[0.005196771,0.0003469887,0.0002671489,0.0006546283,0.004884928,0.009166252,0.001042784,0.003598103,0.005302249],"category_scores_gemma":[0.004860673,0.0001457165,0.0004750476,0.001055174,0.009202464,0.005281779,0.005652884,0.003834907,0.0007369115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006166151,"about_ca_system_score_gemma":0.0109078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02261125,"about_ca_topic_score_gemma":0.03028344,"domain_scores_codex":[0.9979125,0.0009699444,0.00009427306,0.000221687,0.0002253269,0.0005763654],"domain_scores_gemma":[0.9982797,0.000414214,0.0002294151,0.0001657535,0.0004066112,0.0005043098],"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":[0.00002285233,0.00003045913,0.003614783,0.0001431459,0.00001772626,0.0002497144,0.01327834,0.002123637,0.0003328631,0.9175968,0.04131043,0.02127936],"study_design_scores_gemma":[0.00001138286,0.00006606572,0.004774949,0.001155129,0.00002107688,0.0001762083,0.04871425,0.001664565,0.0004472147,0.4276531,0.5152501,0.00006592675],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1116882,0.01315502,0.01159223,0.4174775,0.005154732,0.0001253015,0.0003886576,0.0001699568,0.4402484],"genre_scores_gemma":[0.938808,0.007302074,0.004871168,0.02434902,0.0008628399,0.0001551459,0.0001703894,0.00009306593,0.02338831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02261125,"threshold_uncertainty_score":0.04495931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01627318665159033,"score_gpt":0.3076507411796378,"score_spread":0.2913775545280474,"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."}}