SOCIAL FUNCTIONS IN THE SOCIOLINGUISTIC TYPOLOGY (ON THE MATERIAL OF THE LANGUAGES OF THE RUSSIAN FEDERATION)
Bibliographic record
Abstract
The article describes the current state of social linguistics in Russia, its achievements and promising areas for further development.What seems obvious is a relatively small number of scientific works that focus on the methods and techniques of sociolinguistic research and works on typology, including the question of the principles of creating a typological classification of languages.An attempt to create such a classification was presented in a six-volume international work on the languages of the peoples of the world (published in Canada 2000, 2003, Quebec, Laval University).However, this work was not completed and was limited only to an inventory of the social functions of a number of world languages.The article proposes to develop the principles of a functional classification based on the material of the languages of Russia.For this purpose, the descriptions of social functions in the Canadian-Russian work, the encyclopaedia "Language and Society" will be used, as well as data from sociolinguistic studies of the languages of Russia.Social functions can be measured using the method of calculating the demographic and communicative power of languages.The authors believe that the development of such a classification, its scientific basis will lead not only to the development of sociolinguistics, but can also become a prerequisite for its further progress.The paper analyzes the principles of identifying the functional types of languages, considers the integral and differential features of different groups, identified on the basis of the social functions of the languages of Russia.The authors distinguish seven functional types, starting with a language with global social functions (Russian), and ending with the languages of temporary linguistic communities (migrants and migrant laborers).At the same time, the authors consider the social functions of the Russian language in different linguistic communities, including communities situated outside the territory of Russia.The languages of the second functional type are further analyzed, such as Tatar language, Tuvinian language, Chuvash language, Bashkir language, Yakut language, languages of minorities and languages of migrants.In conclusion, a description of the multi-component socio-communicative system of the Russian Federation is given and it is concluded that the basic principles of the classification of Russian languages can be used to analyse the linguistic diversity in other regions of the world.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".