Canadian Immersion Education in an Evaluative Perspective: A Synthesis of Research Findings on the Efficiency of French Immersion Programmes(1)
Bibliographic record
Abstract
The purpose of the present study is to synthesize research findings accumulated by numerous evaluation studies on the efficiency of French immersion programmes in Canada. The synthesis has been attempted in terms of the four different, but related perspectives; effects on French language skills, effects on English language skills, effects on general scholastic achievements, and effects on socio-cultural domains. Out of these four perspectives, the present paper, the first of the series of two, has focused on the first two perspectives of linguistic nature. Accordingly, it has focused, first, on research findings presented by those evaluation studies that compared students' performance in French between French immersion programmes and regular English programmes, between French immersion programmes and programmes for French-speaking students, and between different types of French immersion programmes. Secondly, it has focused on research findings from those evaluation studies that compared students' performance in English in a similar framework. A close examination of these research findings has revealed that in both perspectives the efficiency of French immersion programmes is well attested, endorsing the claim by supporters of French immersion programmes for the achievement of functional bilingualism in French and English among immersion graduates.
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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 | 0.035 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| 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".