Comparative legal studies of linguistic relations between the indigenous peoples of the Russia and the aboriginal peoples of Canada: The Scientific basis for improving russian legislation
Bibliographic record
Abstract
The International Decade of Indigenous Languages, launched in 2022 under the auspices of UNESCO, has predetermined a significant increase in both activities for the preservation and revitalisation of minority languages around the world, the improvement of national and international legislation regulating language relations, and an increase in the number of scientific studies in this field. Changes in language legislation both in the Russian Federation and in large multi-ethnic countries testify to significant shifts in global trends in language policy based on new scientific and statistical data. In this connection, comparative legal studies of the language relations of such countries, among which Canada acquires the greatest interest from the scientific point of view, are of particular relevance. Canada has more than sixty autochthonous languages, nine of which are recognised as official languages. The basic legal provisions are enshrined in the federal Official Languages Act of 1988. In addition, Canada, like the Russian Federation, has a federal structure. The insufficient number of scientific studies, the lack of relevant scientific sources, the absence of Russian-language translations of the major sources of Canadian language law and policy, as well as radical transformations in political views and approaches to the development of language policy in Canada necessitates an increase in comparative legal research, which can provide valuable scientific material for the development of domestic language legislation and linguistic security in the context of the transformation of international politics.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".