The Copy Effect in Translation: On Formal Similarity and the Book Historic Perspective
Bibliographic record
Abstract
This study takes up the perspective of material book history to revisit the paradox of identity and difference that has always been central to translation. I will argue here that a cognitive effect of identity in translation—which I am calling the “copy effect”—remains to be grappled with theoretically in its own right, and that contemporary theory has generally used the idea of “identity” in translation as a mute antithesis from which to repel with discourse privileging variance and difference. My goal here is to talk about the identity inherent in any translation, and the powerful effect of formal identity that a good number of translations display. First, I will address the paradox itself. Then I will draw attention to the material side of the verbal and linguistic and make a sharp distinction between two types of “form” that textual discourse can take: (1) a “stylistic form” that is qualitative and that translators feel free to vary; and (2) a “Pythagorean form” that is primarily quantitative and derived from textual materiality, and that translators tend to map over with a stricter attention to invariance. Translation scholars, we will see, have been reluctant to distinguish between these two types of form, which has resulted in denials and elisions conflicting with the material evidence of translation. Then I will pursue this material perspective on translation and seek out discourse situating a “copy effect” historically and culturally. This will lead to a discussion of Rita Copeland’s connection between translation and the classical and medieval copia verborum. Finally, I will enter into a new line of reflection opened by Anthony Pym, and propose that through the copia verborum and its historic and contemporary use in construing literalist translations, a compelling analogy can be drawn between medieval translation practices and modern-day digital ones using translation memories.
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.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.048 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".