Russian as native, non-native, one of natives and foreign languages: Questions of terminology and measurement of levels of proficiency
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
© 2015, Canadian Center of Science and Education. All rights reserved. The 21st century has brought globalization of people’s lives and education. Dramatic economical, political and natural cataclysms has made our planet’s population mobile and that concerns not only highly developed countries but also so called the third world countries. While moving and changing their places of residence people bring with them their native language, their culture, knowledge and experience. They also bring to their new county of residence their own perception about communication, both an inner communication and an intercultural one. Bulat Okudzhava said in one of his poems, “To understand each other is a sacred science”, and today this approach to communication becomes a vital necessity in everyday life, in the sphere of science and education, in real space as well as in the virtual one. While people actively learn foreign languages with approved status, minor languages become suppressed in spite of the fact that the population - bearers of these minor languages are quite numerous and these bearers should be taken into consideration. But this problem is likely to be referred to politics. In the frames of practical educational activities we deal with various problems. One of them quite often causes obstacles not only in organizing of the methodically correct educational process but also in its monitoring process. Its impact on marking the final results, on achieving targeted competences - all these are the subjects of correct terminology. To be more precise – correlation of terminology that is accepted in Russian Federation and in the world (in the first place in Europe, the USA, Israel).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.019 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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