Bi-directionality in the Language Combinations of English Conference Interpreters in English-speaking North America: Expectations and Reality
Bibliographic record
Abstract
Sur le marché européen, les interprètes dont l’anglais est la langue A sont souvent encouragés à travailler depuis autant de langues C que possible. Ce mémoire examine ainsi la situation aux États-Unis et au Canada, deux pays où l’anglais prédomine, afin de déterminer si le fait d’avoir une deuxième langue active est un avantage significatif sur ces marchés. Une vérification empirique des combinaisons de langue des interprètes de l’AIIC et des programmes de formation validés par l’AIIC aux États-Unis et au Canada a montré que les interprètes anglophones doivent ou sont encouragés à détenir une deuxième langue active en plus de l’anglais. Au Canada, celle-ci sera plutôt le français alors qu’on préfèrera l’espagnol aux États-Unis.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".