Aspects d’oralité dans l’écriture romanesque d’Alain Mabanckou
Bibliographic record
Abstract
L’objectif principal de cet article est de montrer, à partir d’illustrations tirées des romans African Psycho, Verre Cassé, Mémoires de porc-épicet Black Bazard’Alain Mabanckou, que l’oralité influe profondément sur l’orthographe. Cet auteur transcrit les sons dans le tissu textuel de ses romans. À l’ère de nouvelles technologies de l’information et de la communication, mieux de l’internet, rendu performant par la structuration de la fibre optique, l’envoi des messages (sms) téléphoniques consacre un culte à la perversion orthographique dans les structures phrastiques. Cette tendance à travestir l’orthographe, de plus en plus répandue chez les auteurs francophones, présage une variété de langue française affranchie des normes rigoureuses qui, jusqu’ici, l’ont régie, comme le signale Charles Bally (1932; p. 25 ) : « Il y a une pathologie linguistique qui est une exagération du fonctionnement normal » du français. Le français moderne est-il vu comme une langue peu rigoureuse, moins surveillée donc licencieuse?
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".