Considérations syntaxico-sémantiques de l’utilisation du verbe gérer dans le français ivoirien
Bibliographic record
Abstract
Le verbe gérer, tel qu’il est utilisé par les Ivoiriens, présente des caractéristiques syntaxiques et sémantiques particulières par rapport à celles du français standard. Pour bien comprendre le phénomène, nous avons enquêté trois catégories d’usagers du français : les élèves et étudiants, les locuteurs peu on non lettrés et enfin les cadres subalternes de l’administration et les universitaires. L’analyse du corpus oral a révélé un emploi abusif de gérer par les locuteurs là où on attend d’autres concepts. En fait, les énonciateurs agissent comme si ces termes du français standard ne parviennent pas à traduire explicitement la sensibilité et la culture ivoirienne. Mais cette trouvaille produit des néologismes suffisamment riches. Ils témoignent en même temps de la vitalité du français dans le pays au moment où chaque communauté francophone se bat pour légitimer au sein de la francophonie ses propres usances. The verb « gérer », as used by Ivorians, shows particular syntactic and semantic characteristics compared to those of standard French. To understand this phenomenon, we studied the discourse of three categories of French speakers : pupils and students, semiliterate and illiterate speakers, and finally administration officials and university teachers. The analysis of oral corpus revealed a misuse of the verb « gérer », where other concepts are expected. In fact, speakers act as if these terms of standard French fail to explicitly reflect the sensitivity and the Ivorian culture. But this discovery produces rather rich neologisms. They show the same time the vitality of French in the country when each French-speaking community is struggling to legitimize its own customary practices.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".