Bibliographic record
Abstract
Le compliment a déjà fait l’objet d’une littérature abondante. Et si les formulations du compliment répertoriées jusqu’à date sont nombreuses et variées, elles proviennent essentiellement des espaces culturels européens, américains et asiatiques. L’énoncé laudatif en contexte camerounais a très peu retenu l’attention des chercheurs. Cette contribution a pour but de montrer comment le locuteur francophone gère le matériau linguistique à sa disposition pour « trousser » ses compliments. Nous tenterons en effet de décrire les procédés lexicaux, syntaxiques et stylistiques que le laudateur met en œuvre pour dévoiler et faire accepter son « but illocutoire. » Les analyses permettront de voir que l’expression de l’admiration en français au Cameroun a lieu à travers des formes lexico-sémantiques et stylistiques marquées par l’alternance codique, l’emprunt, le calque, l’argot et le recours aux énoncés laudatifs explicites, implicites et complexes.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".