Prosodic Transfer in Contact Varieties: Vocative Calls in Metropolitan and Basaá-Cameroonian French
Bibliographic record
Abstract
This paper examines the production of vocative calls in (Northern) Metropolitan French (MF) and Cameroonian French (CF) as it is spoken by native speakers of a tone language, Basaá. While the results of our Discourse Completion Task confirm previous descriptions of MF, they also further our understanding of the relationship between pragmatics and prosody across different groups of French speakers. MF favors the vocative chant in routine contexts and a rising-falling contour in urgent contexts. In contrast, context has little influence on the choice of contour in CF. A melody consisting of the surface realization of lexical tones is produced in both contexts. Regarding acoustic parameters, context only exerts a significant effect on the loudness of vocative calls (RMS amplitude) and has little effect on their F0 height, F0 range and duration. A target-use of vocative calls in CF thus does not amount to target-like use of the original standard target language, MF. Our results provide novel evidence for the transfer of lexical tones onto the contact variety of an intonation language. They also corroborate previous studies involving the pragmatics-prosody interface: the more marked a prosodic pattern is (here, the vocative chant), the more difficult it is to acquire.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".