Particularities of Political Vocabulary in Tatar and Mari Mass Media: Synchronic and Diachronic Analysis
Bibliographic record
Abstract
Politics, like any other social sphere, is served by a distinct system of lexical resources, namely—political vocabulary. The article examines semantical and structural organisation of political vocabulary in two languages —Tatar and Mari—both from a historical perspective and at the present stage of their development. Lexico-semantic groups expressing the concepts of “power” and “politician” are thoroughly explored. The following dominant ways of political vocabulary formation are identified: morphological, morpho-syntactic, lexico-grammatical and phono-morphological. Political lexemes deriving from Altai, Turkic and Tatar strata are investigated. Borrowings in the political vocabulary are carefully examined, data drawn from the leading Tatar- and Mari-medium newspapers. The article also covers a study of functioning of the political vocabulary related to the concepts of “power” and “politician”, such as: state / country, government, political party / movement, heads of state departments, elections.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".