Reconciling Institutional and Professional Requirements in the Specialised Inverse Translation Class – A Case Study
Bibliographic record
Abstract
Translating into a language that is not one’s native language is no easy task, but one which may be necessary in certain settings. If a market niche exists for professional translators whose working language is not their native language, as studies have shown it does in Spain, it seems appropriate that translation trainees should be encouraged to develop their competence in what is generally known in Translation Studies as inverse (A-B/C) translation, in order to satisfy market requirements. Given current European Higher Education Area (EHEA) requirements for training students for the professional workplace, most translation degree programs in universities in Spain include subjects in which students are required to translate into the foreign language. This paper describes an early attempt to reconcile institutional requirements (curriculum design, assessment, reporting) and professional requirements (development of translation and instrumental competences, together with so-called soft skills ) in the specialised inverse translation class in the Faculty of Translation and Interpreting of the Universitat Autònoma de Barcelona. A competence-based, learner-centred, process-oriented curriculum was instituted.
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 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".