{"id":"W7164881142","doi":"10.1080/17153379.2015.12557426","title":"Seeing Transnationally: How Chinese Migrants Make Their Dreams Come True. Global Migration and China.","year":2015,"lang":"en","type":"article","venue":"Pacific Affairs","topic":"Diaspora, migration, transnational identity","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration; Irregular migration; China; Human migration","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001485799,0.0002396201,0.0001420985,0.0004565006,0.007295546,0.005786635,0.0004968816,0.001063857,0.004867718],"category_scores_gemma":[0.001824627,0.0001734207,0.000167882,0.0008122409,0.009253642,0.005238605,0.003007152,0.002085733,0.0003198134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001979364,"about_ca_system_score_gemma":0.005615692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05708106,"about_ca_topic_score_gemma":0.127115,"domain_scores_codex":[0.9995479,0.0002337044,0.000009136792,0.00003391151,0.00004321704,0.000131992],"domain_scores_gemma":[0.999375,0.0001762435,0.00006146287,0.00005380524,0.00008480476,0.0002486873],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004610006,0.00003928254,0.01555453,0.0001231067,0.0000132028,0.0005979781,0.8198859,0.00007962453,0.0004116455,0.08771739,0.02053966,0.05499159],"study_design_scores_gemma":[0.000005581607,0.00002561286,0.01760816,0.0001241139,0.00001921532,0.0001255028,0.8941295,0.0001108414,0.0002165404,0.01488939,0.07272638,0.00001929608],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6620671,0.01336507,0.001057886,0.1135455,0.0008823284,0.00003260199,0.000139597,0.00005665951,0.2088534],"genre_scores_gemma":[0.9847607,0.002384228,0.0002090532,0.001481352,0.00003908859,0.00001273094,0.00001842459,0.000009338176,0.01108507],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05708106,"threshold_uncertainty_score":0.1134977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02012582038459616,"score_gpt":0.2731700074953087,"score_spread":0.2530441871107125,"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."}}