The Role of Intermediary Language at the Lessons of Russian as a Foreign Language in the Context of a Present-Day University
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The article considers the feasibility of using the intermediary language in Russian as a foreign language lessons with students of the English department. It is concluded that at the initial stage of training, an intermediary language is necessary: it performs a number of important functions, allows a comparative analysis of language phenomena, and helps to overcome interference. Thus, for a teacher of Russian as a foreign language, good command of the English language becomes a necessary professional skill, and the creation of new nationally oriented teaching aids in Russian as a foreign language is one of the main tasks of the modern methodology of teaching foreign languages. The article also presents the results of a survey of 178 foreign students on the most relevant aspects of the problem being studied.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it