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Record W4405597456 · doi:10.1075/sar.23014.ish

Language learning, desire, and global power dynamics

2024· article· en· W4405597456 on OpenAlexfundaboutno aff
Aika Ishige

Bibliographic record

VenueStudy Abroad Research in Second Language Acquisition and International Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsAmbivalenceDynamics (music)NarrativePower (physics)Participant observationPerceptionSociologyQualitative researchStudy abroadGender studiesPsychologyPedagogyLinguisticsSocial psychologySocial science

Abstract

fetched live from OpenAlex

Abstract Drawing on the concepts of desire from applied linguistics and Deleuzian perspectives, this study investigates the desires encapsulated in a Japanese woman’s English learning sojourn in the Philippines. Data were collected using an open-ended questionnaire and through two semi-structured interviews. The participant’s retrospective narrative provides insight into her perceptions of the Philippines compared to Canada. While previous research has primarily examined the sociolinguistic aspects of studying abroad in the Philippines, the current study expands this focus to encompass other dimensions, such as material factors. The findings illuminate how the Philippines, as a study-abroad destination, is experienced and remembered by students. Further, the findings unveil the participant’s ambivalent yet irresistible akogare for the West. The marginal desirability of the Philippines as a study-abroad destination represents how the historically and economically constituted global hierarchies of power have been reproduced in the discourse and practice of transnational English learning.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.058
GPT teacher head0.547
Teacher spread0.489 · 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 teacher head, not a consensus.

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
Published2024
Admission routes2
Has abstractyes

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