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Record W3011821470

The Figured World of Globalization and Cosmopolitanism and Korean Temporary Migrant Parents` Practices of their Children`s Language Education

2010· article· en· W3011821470 on OpenAlexvenueno aff
Ka Youn Chung

Bibliographic record

VenueEarly childhood education · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsCosmopolitanismNarrativeGlobalizationEthnographyIdeologyConstruct (python library)SociologyGender studiesNarrative inquiryPerspective (graphical)PsychologyPolitical scienceAnthropologyLiterature
DOInot available

Abstract

fetched live from OpenAlex

This study explores Korean parents` narratives and practices for their children`s English education through the theoretical lens of “figured worlds” (Holland, Skinner, Lachicotte, and Cain, 1998). Figured worlds, collectively shared sets of ideologies and practices among members of a group, help to analyze the practice from the participant`s perspective. The study focuses on Korean temporary migrant families with 3- to 8-year-old children who have already arrived in the United States. From 2003 to 2006, I conducted an ethnographic study of Korean international families in a university town in the Midwest. I investigated what motivates parents to implement this extreme practice of English education, that is, migration. The analysis discloses the parents have somewhat exaggerated beliefs on effectiveness of English education for their children. Those beliefs have been justified and intensified through their shared narrative in the figured worlds of globalization and cosmopolitanism. The parents also construct this narrative by psychologically interacting with their past experience and present situation.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.006
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.361
Teacher spread0.347 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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