Transnational Translation: Reflections on Translating from Judeo-Spanish and Spanglish
Bibliographic record
Abstract
Judeo-Spanish and Spanglish are language varieties of minoritized communities at the geographic and cultural edges of the Spanish-speaking world. Literature is being published in both varieties as a way of carving out a space for the speakers of these varieties in societies (the US and Israel for the most part) that value linguistic homogeneity as a national unifying force. This paper grapples with two challenges that emerge when translating literature motivated by such political motivations into English: 1) translating hybridity and 2) orality. It then goes on to explore a few strategies that I have applied to some translations in an effort to address these challenges. The readers of American English translations have been taught to believe in nation-based categorizations of identity that, while they may be useful in many cases, do not accurately describe the “hybrid” contexts whence these source texts emerged. Similarly, orality is ever-present in language varieties that have been rarely written. Recognizing that a translation strategy for such literature must strive to respond to the cultural realities of both the source and target culture, this paper proposes two strategies that attempt to bring this hybridity and orality to an English reader.
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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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.021 | 0.024 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".