{"id":"W4228999515","doi":"10.1515/applirev-2022-2016","title":"Designing new Korean mothers, daughters-in-law, and wives: an analysis of Korean textbooks for newly arrived marriage migrants in South Korea","year":2022,"lang":"en","type":"article","venue":"Applied Linguistics Review","topic":"Gender Studies in Language","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Nationalism; Gender studies; Wife; Socialization; Immigration; Sociology; Politics; Sociocultural evolution; Representation (politics); State (computer science); Identity (music); Ethnography; Settlement (finance); Political science; Law; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001949461,0.0002354015,0.0009168512,0.0002662005,0.0003939192,0.00003220583,0.0004861219,0.00006240307,0.0001030224],"category_scores_gemma":[0.0009319185,0.000248806,0.0001468445,0.0009055883,0.0003252541,0.00001642182,0.0001678368,0.0002053916,0.000001076072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001554858,"about_ca_system_score_gemma":0.0001540784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004032129,"about_ca_topic_score_gemma":0.007991231,"domain_scores_codex":[0.9976281,0.0002865546,0.0006661947,0.0005324717,0.0004131864,0.0004735011],"domain_scores_gemma":[0.9986191,0.0003795742,0.0003457964,0.0004185213,0.00007195209,0.0001650549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001799891,0.0003596768,0.01564131,0.002148254,0.00122314,0.00007079879,0.4609435,0.001040901,0.0002747204,0.4862948,0.001192147,0.03063073],"study_design_scores_gemma":[0.01012943,0.0008212139,0.00486842,0.003744098,0.01299616,0.000003358752,0.5151628,0.003259717,0.000395349,0.05413122,0.3898225,0.00466571],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05292551,0.219998,0.03241059,0.001130869,0.002526268,0.02591228,0.002219008,0.000556061,0.6623214],"genre_scores_gemma":[0.9811109,0.002609102,0.01468275,0.000984199,0.0001934012,0.0001698165,0.00008620321,0.00003852939,0.0001251506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9281853,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04032226693317117,"score_gpt":0.3262429951221246,"score_spread":0.2859207281889534,"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."}}