Foreword: Translation and Transformission; or, Early Modernity in Motion
Bibliographic record
Abstract
concept of “transformission,” created by Randall McLeod, does indeed “cover most everything.” It proves broadly generative for studying early modernity and is especially applicable to early modern translations, as the essays in this issue demonstrate. The most direct contribution of the idea of transformission to translation studies is procedural: when looking at translations, we should look also at changes made to their material texts. The idea of transformission, however, originated in textual studies and editorial theory, and those origins help us understand its special relevance to translation studies. This Foreword to a special issue on transformission and translation first considers briefly the textual origins of the idea of transformission, particularly examining how the perennial problem of variant versions can be reimagined through the lens of transformission and related textual-studies concepts. From there, the idea of transformission connects readily to translation studies: translations, after all, are variant versions of a work, and they, too, are transformed when transmitted.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".