évaluation en didactique de la traduction: un état des lieux
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
Though didactic assessment constitutes a prominent concern for students, little has been said in Translation Studies literature about it. For instance, this area has not been studied in French-speaking Canada, whether among teachers or students. The objective of this article is to present an up-to-date snapshot of didactic assessment in translation, in a context that has been deeply modified over the last decades due to the now massive presence of technology. The data consist of 389 responses by teachers and students from eight Canadian universities, either through semi-directive interviews or an online questionnaire. According to the findings of the study, the assessment methods currently used have not significantly evolved over the last decades, despite the considerable changes the profession has undergone. These methods are used in an almost monolithic way, independent of the progress of students in their course of study. Since assessment is considered an integral part of the teaching and learning processes, any attempt to rethink the didactic assessment methodology cannot be done without a concomitant reflection on teaching approaches.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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