ТЕНДЕНЦІЇ РОЗВИТКУ ЕМІГРАЦІЙНОГО ШКІЛЬНИЦТВА УПРОДОВЖ ХХ СТОЛІТТЯ
Bibliographic record
Abstract
The article deals with objective and subjective tendencies of development of primary, secondary and higher education in the countries west, inhabited by immigrants from Ukraine. It is proved that during the XX century Ukrainian emigration schooling went that evolutional way, which other nations did in foreign environment. Unlike schools that existed in the USSR, the emigrants kept schools at their own expense and only in some cases the state assumed the obligation to teach Ukrainian children (Czechoslovakia, Canada). In the history of pedagogy the activity of school of Ukrainian studies outside the motherland – is a unique example of preservation of national identity, instilling in the younger generation the knowledge about Ukraine, its customs and traditions. The practice proves that children, who learned early the basics of the Ukrainian language and literature in foreign environment, fluently speak their native language during their lives.
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How this classification was reachedexpand
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; both teacher heads agree on what is shown here.
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".