Learning a foreign language as leisure and consumption: enjoyment, desire, and the business of<i>eikaiwa</i>
Bibliographic record
Abstract
Social inclusion typically refers to the integration of the disadvantaged into the mainstream society as a national agenda. However, social inclusion in a broader sense addresses aspirations to be included in a global imagined community as well as a local community of like-minded people. Drawing on a qualitative study of men and women learning eikaiwa [English conversation] in informal settings in Japan, this paper investigates the aspects of leisure and consumption as characteristics of foreign language learning, rather than investment for gaining cultural capital. This perspective highlights the enjoyment of socializing with the teacher and the peers and forms of akogare [desire/longing] including romantic desire and the aspiration to be like other Japanese people with fluency in English. The manifestations of romantic akogare for white English-speaking men related to learning English were nuanced, diverse, and identified across gender and race. The dimension of leisure and consumption produces and reflects the business interest of the eikaiwa industry which commodifies and exploits whiteness and native speakers. The aspects of leisure and consumption challenge the possibility of critical engagement in foreign language learning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".