Evaluating the Oral Language Skills of English-Stream and French Immersion Students: Are the CLB/NCLC Applicable?
Bibliographic record
Abstract
This study examined the oral language skills of grade-two anglophone children enrolled in French Immersion and English-stream programs. The study had two objectives: (a) to compare performance between the groups on measures of receptive vocabulary, narrative comprehension, and narrative production (i.e., structure and language) in English, and (b) to explore the applicability of the Canadian Language Benchmarks/Niveaux de compétences linguistiques canadiens (CLB/NCLC) to assessment of their conversational competency. All children (English-stream n = 27, French Immersion n = 33, aged 7-8 years) were tested in English. In addition, the French Immersion students were tested using equivalent measures in French. The results comparing performance in English revealed no differences between the groups on receptive vocabulary, narrative comprehension and narrative structure. However, the English-stream children outperformed their French Immersion peers in narrative language. Furthermore, CLB/NCLC listening and speaking criteria were applied to conversational samples yielding level scores in English (both groups) and French (French Immersion only). The range of benchmarks that are appropriate for this population is discussed in detail.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".