Traces of monolingual and plurilingual ideologies in the history of language policies in France
Bibliographic record
Abstract
French is often quoted as the forerunner and model of a very normative and top-down managed language, following the language policy of an archetypal monolingual nation-state, be it France, Quebec or other French-speaking communities in the world. This particular contribution is not going to prove the contrary. However, we will try to show that even the French language and the French-speaking nations are not as much of a monolithic block as they are frequently perceived to be. At different moments in history other ideologies on the French language appeared. They concerned, on the one hand, the relationship between “French” and other languages – historical minorities and immigrant languages – and, on the other hand, the attitudes towards different varieties of French. In other words, the history of French must take into account three different elements: (a) the elaboration, over the centuries, of the endoxa, that is the official ideology, fixed in the dominant discourse; (b) the existence and, at some moments in history, prioritization of other types of discourse, manifesting more or less opposite opinions; (c) the fact that different beliefs may co-exist, that contradictory voices can be heard simultaneously at certain moments and also struggle in the arena of public discourse, enabling the (en)doxa to be polyphonic.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.014 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".