{"id":"W4293443012","doi":"10.1111/imig.13017","title":"Being “top‐ranked” without “causing troubles”: Comparing federal and provincial immigration pathways for Chinese international students in Canada","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":"Carleton University","funders":"","keywords":"Immigration; Deskilling; Human capital; Immigration policy; Selection (genetic algorithm); Demographic economics; Political science; Economic growth; Economics; Work (physics); Law","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000598978,0.0001346003,0.0001516741,0.0001969748,0.0006672769,0.0002912467,0.0002899535,0.00003802115,0.0000890654],"category_scores_gemma":[0.0001518957,0.000151252,0.00004295399,0.0001876371,0.00003266539,0.0004983173,0.0001026675,0.0001731843,5.985754e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001930314,"about_ca_system_score_gemma":0.0007408913,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6548918,"about_ca_topic_score_gemma":0.9960195,"domain_scores_codex":[0.9980047,0.0001287541,0.0003996186,0.0002910942,0.0009666518,0.0002091553],"domain_scores_gemma":[0.9993867,0.0000898346,0.0001911422,0.00007015987,0.0001968675,0.00006531538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001491028,0.0001034918,0.9586264,0.000005223542,0.00003819774,0.000004555641,0.01485505,0.003369795,0.0004920483,0.02051363,0.0002755604,0.001566958],"study_design_scores_gemma":[0.003619045,0.0001058934,0.4080999,0.00005021568,0.00002215897,0.00001335452,0.0271833,0.5233132,0.00007280895,0.005122984,0.03176101,0.0006361948],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990204,0.00001729376,0.002949307,0.003130928,0.001648659,0.0005416387,0.00008404969,0.00003360157,0.001390527],"genre_scores_gemma":[0.9976288,0.00002645349,0.0004637481,0.0004200933,0.0003806167,0.0001871711,0.0004258635,0.00001392274,0.0004533175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5505265,"threshold_uncertainty_score":0.6167877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01358635086577621,"score_gpt":0.2973976249438593,"score_spread":0.2838112740780831,"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."}}