Social and Stylistic Variation in Spoken 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
Many of the assumptions of Labovian sociolinguistics are based on results drawn from US and UK English, Latin American Spanish and Canadian French. Sociolinguistic variation in the French of France has been rather little studied compared to these languages. This volume is the first examination and exploration of variation in French that studies in a unified way the levels of phonology, grammar and lexis using quantitative methods. One of its aims is to establish whether the patterns of variation that have been reported in French conform to those reported in other languages. A second important theme of this volume is the study of variation across speech styles in French, through a comparison with some of the best-known English results. The book is therefore also the first to examine current theories of social-stylistic variation by using fresh quantitative data. These data throw new light on the influence of methodology on results, on why certain linguistic variables have more stylistic value, and on how the strong normative tradition in France moulds interactions between social and stylistic variation.
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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 | 0.001 |
| 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) | 0.001 | 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