On the Translation of Otherness: The Univocal Case of Will Grayson, Will Grayson
Bibliographic record
Abstract
Over the past twenty years, after the LGBT+ liberationist movement has managed to make new voices heard and had certain social gains, partly overturning decades of exclusion and segregation, gay literature has often focused on the stories of young men and women as a form of instilling positive values upon the future generations. The mainstream publishing world in Spanish has sometimes lagged behind LGBT+ times, publishing little queer literature and favoring mainly canonical authors. Translation criticism from the cultural margins raises questions regarding the voices of alterity and, in this respect, it highlights the visibility of translators (and publishing houses) as subjective factors in the translation process. The ideological analysis of literary translation may identify the role of translators as intercultural mediators who use strategies that accentuate or subdue the LGBT+ character of the texts they translate. The young-adult, gay novelWill Grayson, Will Grayson, written by John Green and David Levithan, presents an interesting challenge from the point of view of the separate discursive identities at play in it. Nonetheless, the novel was solely translated by Noemí Sobregués, a situation calling for closer analysis to revise the strategies used to represent the duality of the text in terms of idiolectal authorship. Using the tools provided by Keith Harvey (2000), this paper focuses on the analysis of the role of this translator in the rendition of the novel in Spanish, in the larger context of what it is that publishing houses seek when they publish LGBT+ literature: either to portray watered-down versions palatable to mainstream readerships, or to queerify their publishing catalogues, and thence, possibly, the canon at large.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.029 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| 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".