Formation of lingual identity in preschool institutions of the Republic of Tatarstan
Why this work is in the frame
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Bibliographic record
Abstract
© 2014, Canadian Center of Science and Education. All rights reserved. In the Republic of Tatarstan (Russian Federation) we meet with a certain discrepancy when deal with the problem of lingual identity formation. Therefore the outcomes of coordinated (synchronous, simultaneous) teaching of Russian, Tatar and English languages to preschool level children are to be analysed. In Tatarstan it emerged, on the one hand, from the need to learn three languages rather than two, i.e. Tatar, Russian and English languages at an active speaking level. The problems of lingual identity formation in preschool institutions of the Republic of Tatarstan are depicted. The research showed that children relatively easily and quickly remember the words, learn to use them in their speech, show their interest in differences between the languages. If in the course of the second stage of research 40% of children got high score, then during the third stage 80% revealed good knowledge, which makes the majority of the group. Children recognize familiar words, can name the things, try to make sentences in all three languages. It's quite natural, that not all children can master language material, but there's a tendency that answers of all children become more confident and precise to the third stage of research. At the first stage, children did not understand the difference between the languages. At the second stage children confused languages, made mistakes in their answers, while at the third stage there were far less mistakes. Monitoring is very important in teaching languages, since it allows to estimate the level of mastering language material, to define group of children who feel it difficult to learn languages in order to carry out additional work on subject revision.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 0.010 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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