Was Locke addressing Hobbes or Filmer? How a classical question in the history of political thought may become a tool for understanding the translation of historical texts
Bibliographic record
Abstract
This article aims to rethink the relationship between history and translation by questioning the methodological presuppositions underlying dichotomies taught in Translation Studies, especially that of domestication and foreignization. To this end, we assess the validity of this dichotomy in the case of the translation of historical texts. We argue that research in this field demands a deeper reflection on what could be called “addresseeship”. To engage this claim, we begin by discussing how the classical debate between “textualist” and “contextualist” approaches to the history of political thought can be brought to bear on the issue by virtue of the distinctions that it draws among the various addressees of political texts. We then illustrate this new avenue in the translation of history with a critical account of an original dichotomy proposed by the linguist Dubravko Škiljan between retrospective and prospective translations.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.038 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| 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".