Euphemistic Rhetoric and Dysphemistic Practices: Governing Migration in Mexico
Bibliographic record
Abstract
This paper analyses Mexico’s governance of migration and its geopolitical moral dilemma: an enthusiastic champion for migrants’ human rights in the international sphere and a tough migration control enforcer. I consider this seemingly ambivalent and contradictory approach through the lens of euphemisms and dysphemisms, more specifically by analysing the use of euphemistic rhetoric and dysphemistic practices in the governance of migration. Through document analysis, I examine Mexico’s use of euphemistic rhetoric in its role as migration control enforcer, as well as in its positioning in the relation to the Global Compact on Migration. Drawing on the experiences of irregularised migrants in Mexico and information obtained though Freedom of Information Requests, I analyse three dysphemistic practices in migration management: (i) bureaucratic negligence, (ii) precarious infrastructure, and (iii) spatial fixation and waiting. The Mexican case illustrates the discrepancy between discourse and practice in migration management and is an example of the ambivalences of global migration governance, which instrumentalises euphemistic rhetoric while promoting and tolerating dysphemistic practices.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".