Le Dictionnaire bilingue (anglais-français) de la distribution : entre dictionnaire de langue et encyclopédie
Bibliographic record
Abstract
Les auteurs examinent d'abord la langue de la distribution. L'étude des termes supermarché, hypermarché, très grand supermarché et les "équivalents" anglais leur permet de retracer l'évolution comparative des concepts et de discuter les problèmes soulevés. Ils présentent ensuite leur modèle de microstructure et la méthodologie qui en a guidé la conception, et insistent sur les relations internotionnelles, point central de leur recherche. Ils montrent enfin comment la mise au jour systématique des traits sémantiques qui distinguent les termes et des relations qui les lient les uns aux autres fait naître l'organisation conceptuelle du domaine. C'est par l'explication de cette démarche que l'ouvrage devient un outil de documentation essentiel au travail du traducteur.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".