Bibliographic record
Abstract
Based on fieldwork at a Japanese restaurant in Toronto, this study uncovers the transnational workers’ complex power dynamics that exist behind the façade of jovial translingual practices. Through the multi-layered analysis of the restaurant’s menus, video-recorded staff meetings and worker interviews, we found that linguistic and semiotic resources used to enhance the ethnic identity of the business can cause frictions among the workers, whose linguistic resources are embedded and valued differently at the local and global levels. Japanese managers hold institutional power over the decisions concerning the restaurant’s identity and language policy. These managers, who have limited English skills, actually rely on the creation of a Japanese-dominant space, supported by the global popularity of Japanese cuisine, as a means of survival in the English-dominant local community. The managers depend on English-speaking servers to interact with local customers. On the other hand, the servers, who have limited Japanese skills, consider the restaurant as just a temporary stop on their transnational journey and envision their future as being in the global English-speaking labor market. This study shows how translingual practices, often romanticized as a representation of cosmopolitan conviviality, are built on the precarious grounds of power negotiations and job security among transnationals.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".