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Record W4228999515 · doi:10.1515/applirev-2022-2016

Designing new Korean mothers, daughters-in-law, and wives: an analysis of Korean textbooks for newly arrived marriage migrants in South Korea

2022· article· en· W4228999515 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Linguistics Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGender Studies in Language
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNationalismGender studiesWifeSocializationImmigrationSociologyPoliticsSociocultural evolutionRepresentation (politics)State (computer science)Identity (music)EthnographySettlement (finance)Political scienceLawSocial science

Abstract

fetched live from OpenAlex

Abstract Textbooks are sociocultural materials, reflecting political decisions, educational beliefs and priorities, cultural realities and language policies. As part of a larger ethnographic study which investigated the multilingual socialization of foreign wives in South Korea, I present the nature and extent of the gender-making process through an analysis of Korean textbooks for recently arrived female marriage migrants, which provides an understanding of the extent to which gender and race are ingrained in shaping linguistic nationalism in globalized times. I first introduce a four-stage life cycle designed by the South Korean government and situate Korean textbook series called Korean Language Learning With International Marriage Migrant Women as an intervention used early in the settlement period for foreign mothers. Then, I analyze the textual and multimodal representation of family identities taken from six textbook series, focusing on lessons, dialogues, and characters that are presented. The results of the study demonstrate how the state presents its attempts to transform foreign wives into a new type of ‘wise mother good wife’ in the globalized, multilingual world. I demonstrate the ways in which state-driven gender identity production is not simply (re)producing the gender divide but also aligned with nation-making processes that are facing challenges in these globalized times.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.040
GPT teacher head0.326
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it