{"id":"W7164885909","doi":"10.1080/17153379.2013.12556918","title":"Making and Faking Kinship: Marriage and Labor Migration between China and South Korea.","year":2013,"lang":"en","type":"article","venue":"Pacific Affairs","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"China; Labor relations; Labor disputes; Developed country","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":[0.0009031124,0.0001185553,0.00009704977,0.0004705743,0.001562895,0.0009284097,0.0002747793,0.000373597,0.003782287],"category_scores_gemma":[0.003975933,0.0001122882,0.00008677244,0.0005225654,0.001005269,0.001188149,0.0009854978,0.000659478,0.0002378799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005096556,"about_ca_system_score_gemma":0.0008859876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02643923,"about_ca_topic_score_gemma":0.08717373,"domain_scores_codex":[0.999637,0.0001638428,0.00002037289,0.00003227395,0.00004098208,0.0001054342],"domain_scores_gemma":[0.9976525,0.0005495891,0.001078138,0.0001543527,0.0001698898,0.0003956559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000168573,0.000104069,0.932952,0.00003002084,0.00002197264,0.0003469179,0.03867789,0.0001359248,0.0004051791,0.002001811,0.0007675248,0.02438824],"study_design_scores_gemma":[0.000004310901,0.00006677901,0.8793321,0.00003663965,0.00001571706,0.0001701761,0.1168202,0.0004973329,0.0001957187,0.0007554907,0.002092565,0.00001298403],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986985,0.00006909177,0.00002350139,0.0002244587,0.000004145379,0.000002473766,0.00002836015,3.121405e-7,0.0009490755],"genre_scores_gemma":[0.999326,0.00007057012,0.0000233773,0.0000260065,0.000001917667,0.000001554121,0.00001874207,3.724125e-7,0.0005314444],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02643923,"threshold_uncertainty_score":0.05257064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03614410551825544,"score_gpt":0.2795472766550561,"score_spread":0.2434031711368007,"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."}}