Bibliographic record
Abstract
Referenced by theory for seemingly contradictory purposes, the practice of “surface translation” has an ambivalent status within Translation Studies. This is not surprising, as the principle of ambivalence informs both its composition and its conversation with its reader. Nevertheless, a positive step toward a more productive conception of surface translation was accomplished by Jean-Jacques Lecercle (1990), who defined it as a formin extremisof linguistic interference or mixing. Guided by this conception, I would argue here that the practice is in all respects identifiable with the Classical and Medieval ornamental style known by art history as the “grotesque.” This is the first study to identify surface translation with the grotesque. Five specific points of comparison are leveraged here: 1) Both surface translation and grotesque art are created through the proscribed mixing of incompatible materials; 2) Both are peripheral art forms involving play with margins; 3) Both aspire toward the “perverse,” “comic,” and/or “monstrous” in their mixes; 4) Both tend to be explained as the product of impulsive thinking; 5) The experience that these mixtures are designed to produce is “ambivalence.”
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".