<i>‘Les anglicismes polluent la langue française’</i>. Purist attitudes in France and Quebec
Bibliographic record
Abstract
ABSTRACT It is often claimed that France is a particularly purist country; the Académie française is seen to be representative of a purist outlook and popular works such as Étiemble's attack on English influence Parlez vous franglais? (Étiemble, 1964) have served to bolster this view. However, this claim has not been empirically verified. In order to determine whether or not the rhetoric around purism in France matches the reality, we developed a questionnaire to investigate whether or not ordinary speakers of French in France are purist, taking the theoretical framework in George Thomas's Linguistic Purism as a base (Thomas, 1991). This questionnaire was distributed online to a random sample of participants in France. To contextualise the findings, the questionnaire was also distributed to French speakers in Quebec. The results of the study show that, contrary to expectations, the French respondents display only mild purism and the Québécois respondents are more purist in the face of English borrowings (external purism). However, the French respondents are more concerned with the structure or ‘quality’ of the French language itself (internal purism) than their Québécois counterparts. This study also highlights some problems with Thomas's framework, which requires some modification for future research.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".