Controlling Roma refugees with ‘Google-Hungarian’: Indexing deviance, contempt, and belonging in Toronto's linguistic landscape
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.
Bibliographic record
Abstract
Abstract This article investigates signage in the linguistic landscape of Toronto that is addressed to Hungarian-speaking Roma asylum applicants, focusing on multilingual public-order signs that convey warnings or prohibitions. Such signs are produced by institutional agents who often use machine translation (Google Translate), yielding ungrammatical texts in ostensible Hungarian. Drawing on ethnographic interviews, the article explores the indexicalities that such multilingual signs have for different groups of participants, including Roma addressees and English-speaking ‘overreaders’. While institutions may view the production of multilingual signs as indexical of open-mindedness towards migrants, Roma interviewees may see public-order signs as indexing racial stereotypes by presupposing deviant behavior, and may view ungrammaticality as indexing an unwillingness to engage in face-to-face interaction. (Multilingualism, Canada, Gypsies (Roma), linguistic landscapes, Hungarian, machine translation, indexicality)
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it