Language Policy and Ethnic Tensions in Quebec and Latvia
Bibliographic record
Abstract
This article traces the factors that led to the adoption of the Charter of the French Language in Quebec in 1977 and the Latvian Language Law in 1999. Concerns for the French language in Quebec in the 1960s and 1970s, the Latvian language in the Soviet Union in the late 1980s, and in the Latvian state in the 1990s were ignited by some of the same demographic and assimilative forces in the two societies. Demographic factors included a decline in the birth rate, lower socioeconomic status, and a fear of minoritization in their own respective territories. Schools in English in Quebec and schools in Russian in Latvia attracted most immigrants. To counter these trends, language policies were drafted restricting access to English and Russian languages in schools, on commercial signs, in legislative bodies, and in municipal, public, and para-public administration. Looking for a model to change these conditions, Latvia based a significant part of its language law on the Quebec Charter of the French Language. Significant controversies erupted in both societies with the passage of restrictive language legislation. While the laws have helped to reverse the position of the French and Latvian languages, they have not solved the delicate balance between linguistic communal rights and individual rights.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".