THE DEVELOPMENT OF BILINGUAL EDUCATION IN CANADA
Bibliographic record
Abstract
The article deals with the study of the development of bilingual education in Canada. The research paper offers the results drawn from a broader qualitative study. We understand bilingualism as a linguistic ability of a person, as social circumstances, as social phenomenon or individual characteristics. Bilingual education in Canada is a phenomenon which is based on the integration of theories and concepts of pedagogy, psychology, sociology, history, linguistics and psycholinguistics. The analysis of scientific and pedagogical literature reveals that scientists all over the world research various aspects of bilingualism and development of bilingual education in different countries. According to the aim of the study, theoretical and applied (descriptive, statistical, comparative, inductive, deductive, analytical, logical, historical, chronological and retrospective analysis, prognostic) methods used in our research are presented. We determine and characterise political, historic, economic, social, cultural, religious, lingual factors which caused popularisation and spread of bilingual education in the country under research. We define the lower and upper boundary of our research as well as develop the periodisation of bilingual education development. We characterise the advantages and disadvantages of bilingual education, its main forms, bilingual and traditional programmes, types of immersion programmes, realisation of bilingual education at pre-school, school and university levels.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".