The professional baggage of Translation scholars
Bibliographic record
Abstract
A survey of 305 translation scholars shows that some 96 per cent of them have translated or interpreted “on a regular basis,” with translation/interpreting being or having been a main or secondary activity for 43 percent of the scholars. Translation scholars would also seem to be particularly mobile (71 per cent have spent more than one year in a country other than their own) and come from diverse academic and professional backgrounds (33 percent were not engaged in translation and interpreting in their mid 20s). These figures indicate that translation scholars not only have considerable practical experience of translation but also come from a wide range of occupational and cultural backgrounds. Asked about desirable relations between scholarly work and professional practice, respondents indicated benefits for both sides (although a slight majority stressed a unidirectional relationship where scholarly work benefits from professional practice), and teaching is often indicated as the link between the two. However, about a quarter of the scholars indicated that there need not be a relationship between scholarship and professional practice.
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.
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 | 0.030 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".