Bibliographic record
Abstract
Debate in the Acadian media over the quality of the French language is a recurrent aspect of sociolinguistic life in this region of French Canada. In the fall of 2012, this debate was relaunched by an incendiary newspaper column, written by a Quebec-based journalist, questioning whether the French spoken by young Acadian musicians was really a language at all. Based on twelve interviews conducted shortly after this debate, this article examines how university students in Acadie take up these media discourses about the quality of the French language. In general, the students interviewed regarded the French language as inherently rule-bound and structured, in contrast to English, which many held to be comparatively without rules, even easygoing. The author suggests that this particular view has developed in part because of exposure to discussion over the quality of French in Acadie, and that any attempt to improve what is perceived as the poor quality of French in Acadie cannot ignore the very terms in which it portrays the French language. These figurations become part of the linguistic ideologies of young French speakers in Acadie and potentially feed into the very state of affairs that commentators lament.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.017 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".