Beyond Time on Task: Strategy Use and Development in Intensive Core French
Bibliographic record
Abstract
French Second Language (FSL) learning in the province of New Brunswick (NB) has a history of change and development. As Canada's only official bilingual province, the importance of learning both official languages has been and continues to be at the forefront of many educational initiatives. Since 1987, the core French program has been compulsory from Grade 1 to Grade 10 inclusive. The core French program is one that dedicates a minimum of 30 minutes of FSL instruction per day in elementary school, 40 minutes per day in middle school, and one semester per year in high school for a total of approximately 1065 hours of instruction (NB Department of Education, 2001). Elementary school in NB begins at Kindergarten and ends in grade five although core French is usually not offered before grade one. An internal report published by the NB Department of Education in 1979 indicated that only 61% of core French Students achieved an oral proficiency rating1 higher than Basic (Rehorick, 1993). Since that time, subsequent reports have prompted an increase of attention to and improvement of core French programs through curriculum and professional development initiatives including a focus on raising the standards related to language levels and methodology of FSL teachers. In 1993, oral proficiency ratings for core French students improved somewhat with 45.3 % achieving a Novice level;
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".