A final note on culture, Quebec native languages and the Quebec question
Bibliographic record
Abstract
With Israel and Catalonia, Quebec is considered to be one of the success stories of language planning.These positive results can be explained by the conjonction of three factors, as highlighted by the contributions to this volume.French has always been spoken in Quebec by a significant number of people.These people have always been a majority over the whole of the continuous territory of the province.This territory is managed by a democratically appointed government having some jurisdiction over a wide range of issues.To some degree, these elements presuppose one another.The existence of a government rests on some generally continuous stretch of land -although examples of enclaves are given by Palestine and a few other administrations.The importance of territorial continuity is illustrated in the Canadian context by arguments around the perspective of an independent Quebec : Canadian Federalists refuse the physical separation of Atlantic Provinces from the rest of the country by a sovereign Quebec ; Quebec Sovereignist have always opposed the partition of the provincial territory.Territorial distribution influences the cohesion of a linguistic community.The bond between groups speaking the same language in distinct lands tends to loosen (as between French Canadian communities of Quebec origins and Quebecers themselves), and the languages themselves can differentiate to some degree (as with Portugal and Brazil Portuguese), even where a mere border separates the groups (as with Flemish and Dutch).Especially in those cases where they constitute a majority over a given territory, cohesive groups can in turn determine the agenda of the democratic government that represents them, as illustrated by the Quebec language laws themselves.The governmental, territorial and demographic factors made it possible to transform French from the language of use of a local majority into the official common public language of all Quebecers.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.011 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".