The Beginning Translator's Workbook: Or, The ABCs of French to English Translation <i>The Beginning Translator's Workbook: Or, The ABCs of French to English Translation</i> . By M <scp>ichele</scp> H. J <scp>ones</scp> . Rev. ed. Lanham, MD: University Press of America, 2014. xxii + 291 pp.
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
This book is aimed at translation courses for ‘beginners with a proficiency in French ranging from intermediate to advanced’ offering ‘methodology and practice concurrently’ (p. ix). As such, it endeavours to provide an account of the strategies used by professionals when translating, as well as the significant differences between French and English. Regarding the latter, it lies firmly in the current of comparative stylistics, in which Jean-Paul Vinay and Jean Darbelnet's Stylistique comparée du français et de l'anglais: méthode de traduction (Paris: Didier, 1958) is canonical. Indeed, the core of Michele Jones's book is based around Vinay and Darbelnet's seven translation procedures (from borrowing to adaptation). However, it is disappointing that Jones does not refer to the Canadian authors at all, apart from a reference in the final section on further reading; specific reference to the Stylistique comparée would clarify some of the issues that Jones presents, such as the difference between modulation and equivalence as procedures. Vinay and Darbelnet's emphasis on the situation of the text would significantly help Jones to overcome one of the main deficiencies of this work as a tool for translator-training: it is not until p. 184 that a significant fragment of text is offered as an exercise. Until this point the exercises are isolated sentences that focus on just one translation procedure at a time, and are designed to admit only one response, offering a rather prescriptive method. This is indicative of a greater problem with the text as a method, but also where its main strength lies: Jones frequently deals with obligatory (and arbitrary) shifts between French and English. These lists of common differences between French and English have value, and are particularly useful as raw material for undergraduate language classes (and possibly as revision for postgraduate students of translation). However, their classification according to Vinay and Darbelnet's procedures means that they share the same criticisms, especially that the ‘procedures’ are not actually procedures for translation at all (and thus are not translation strategies), but rather labels placed on differences between the two languages. So, the list of French verb phrases that become single-word verbs in English (and vice versa, p. 3) is useful, but it does not indicate any sort of underlying approach apart from having to learn all examples by rote.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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