Same process, different meaning: /ε/ lowering over time in Louisiana Regional French
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT This paper examines /ɛ/ lowering before /r/ in Louisiana Regional French (e.g., père , /pɛr/ → [pær], [pɛr] ‘father’) between 1977 and 2011 in a small geographic region. The analysis of 436 tokens from 32 speakers shows that /ɛ/ lowering has changed through time from a generational to a geographical boundary marker. This explains differing /ɛ/ lowering rates reported in the literature (Guilbeau, 1950; Dubois, 2005; Salmon, 2009). Results confirm that sociolinguistic factors play an active role in Louisiana Regional French, despite its endangered status (Dajko, 2009; Dubois, 2005), underscoring the need to better control for diatopic factors in future research.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it