Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACTRevision by a second translator plays a major role in quality control in institutional settings such as the European Commission and the United Nations. Different institutional translation services take different approaches to revision, and their approach changes over time. There are policy differences and there are differences among revisers in revision technique. Is there a best way to approach the task, a way which is as fast as possible while achieving adequate quality? Or does it depend on differing institutional requirements and budgets, different conceptions of quality, differences in staff size, and differences in the way individuals process language? If there is no best way of revising, are there ways that do not work well? Surveys of research on revision by a second translator have led to findings which, while interesting, are mostly not of a kind that, if pursued, could provide managers and revisers with a scientific basis for adopting a revision policy or recommending a revision technique. Given a certain concept of Applied Translation Studies, it should be possible, with cooperation and funding from the big translating institutions, for teams of researchers and practitioners to test hypotheses about which of a pair of techniques or policies is best.KEYWORDS: Institutional translationrevision policyrevision techniqueresearchApplied Translation Studies Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The mission of the American Association for Applied Linguistics, according to its website, is 'to facilitate the advancement and dissemination of knowledge and understanding regarding […] language-related issues in order to improve the lives of individuals and conditions in society' (American Association for Applied Linguistics, Citation2018, n.p.). The field 'draws on a wide range of theoretical and methodological approaches from various disciplines – from the humanities to the social and natural sciences – as it develops its own knowledge-base about language, its users and uses, and their underlying social and material conditions' (American Association for Applied Linguistics, Citation2018).2 Quality assessment is perhaps one of the topics Holmes meant by his reference to Criticism of translations, though he was more likely thinking of literary critics reviewing translated novels and poems.3 Studies with professional editors have shown that people can read faster and detect more errors on paper than on screen because the quality of print is still greater (Dayton, Citation2011).4 I worked as a reviser, translator and trainer at the Translation Bureau from 1974 to 2014. I have also led workshops for revisers at the European Commission (2003, 2009 and 2021), the Bank for International Settlements (2013), the Swiss Foreign Ministry (2018), UN Headquarters (2017, 2018), and the International Maritime Organization (2021).5 Reviser reads the translation aloud; translator or speech synthesizer reads the translation aloud while reviser checks it against the source6 Holmes' notion of policy as part of Applied TS was very different from what the term means in the present section. He meant "providing advice to others in defining the place and role of translators, translating, and translation in society at large: such questions, for instance, as determining [what] the social and economic position of the translator is and should be, or what part translating should play in the teaching and learning of foreign languages." (Citation1988, 78).Additional informationNotes on contributorsBrian MossopBrian Mossop worked as a translator, reviser and trainer at the Canadian Government's Translation Bureau from 1974 to 2014. He teaches revision and specialized translation at York University's School of Translation in Toronto, and he is the author of the widely used textbook Revising and Editing for Translators (Routledge, 4th edition 2020).
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.023 | 0.000 |
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 it