{"id":"W2253595205","doi":"10.1111/imig.12234","title":"What Moves the Highly Skilled and Why? Comparing Turkish Nationals in Canada and Germany","year":2016,"lang":"en","type":"article","venue":"International Migration","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Turkish; Affect (linguistics); Political science; Demographic economics; Economics; Sociology","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":[0.00111609,0.0002352829,0.0003173838,0.001347691,0.006053082,0.002266567,0.0007945263,0.0006973336,0.002404868],"category_scores_gemma":[0.002547399,0.0001695793,0.0002250723,0.001998977,0.002692156,0.0007187175,0.001513667,0.0007444141,0.0001480883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02046638,"about_ca_system_score_gemma":0.0237801,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9527037,"about_ca_topic_score_gemma":0.9821156,"domain_scores_codex":[0.9986303,0.0002027806,0.00003681906,0.0001162211,0.0001579867,0.0008560161],"domain_scores_gemma":[0.9986343,0.0002446783,0.0002492863,0.00003169906,0.0004312974,0.0004086777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0002564358,0.0001110573,0.4653343,0.0002433194,0.00005029739,0.001581726,0.4938123,0.000402258,0.001473059,0.006407333,0.003761129,0.02656681],"study_design_scores_gemma":[0.000003588247,0.00001725078,0.2059046,0.0001244604,0.0000132222,0.00008846394,0.7861592,0.0001749453,0.0001637728,0.0001164621,0.007202284,0.00003177397],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962832,0.0001978977,0.00003690296,0.00028983,0.000009969792,0.000009173774,0.00006810375,0.000001156431,0.003103765],"genre_scores_gemma":[0.9980525,0.0002381146,0.00006225255,0.0001090235,0.000001507816,0.000006786237,0.00006951798,0.000002201228,0.001458016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04729635,"threshold_uncertainty_score":0.1484947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.010247193321554,"score_gpt":0.2607720202928973,"score_spread":0.2505248269713433,"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."}}