Bibliographic record
Abstract
Résumé La réputation de l’entreprise est utilisée par le vendeur comme argument de vente et considérée par l’acheteur comme une sorte de garantie de la qualité des produits ou des services qu’il achète. Il est donc primordial pour l’entreprise de bâtir une bonne réputation, de la préserver et, en particulier, de la renforcer pour mieux faire face à la concurrence. Dans le présent article, les auteurs examinent la contribution de deux éléments constitutifs de la confiance du consommateur, à savoir la compétence et la bienveillance, dans le processus de renforcement de la réputation de l’entreprise. Dans un premier temps, le texte montre ce qu’est la réputation de l’entreprise et comment elle peut être formée. Dans un deuxième temps, il met en relief le rôle de la compétence et de la bienveillance de l’entreprise et de son personnel dans l’effort pour accroître la réputation de l’entreprise.
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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".