Berman and Toury: The Translating and Translatability of Research Frameworks
Bibliographic record
Abstract
An initial discussion of Kuhn, Lyotard, and Boothman offers a set of ideas on how and to what extent one research framework can be ‘translated’ into another. Berman’s and Toury’s frameworks for translation research are then examined using some concepts from the above-mentioned theorists, and also concepts from interlingual translation theory. In highly significant ways Berman’s and Toury’s frameworks are incompatible because of the incommensurability of basic ideas underpinning their frameworks. There is, however, some partial equivalence of concepts, in part brought about through evolution of the theories over time. When Berman has ‘translated’ Toury in the sense of discussing his ideas, we find phenomena analogous to those found in interlingual translation: equivalence, transference, shifts, naturalizing, and mistranslation. No doubt if Toury were to ‘translate’ Berman, similar traits would occur. The study supports a nuanced version of Lyotard’s theory: non-absolute incommensurability between discourses or research frameworks.
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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 | 0.040 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.008 | 0.065 |
| Scholarly communication | 0.014 | 0.031 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".