The learning of spoken French variation by immersion students from Toronto, Canada
Bibliographic record
Abstract
This study on the learning of sociolinguistic variants by 41 adolescents from a French immersion program in Toronto, Canada, synthesizes the findings of our research on this topic. This article provides answers to the following questions. First, do the immersion students use the same range of sociolinguistic variants as do speakers of Quebec French, who are used in our research as a first language (L1) benchmark? Second, do they use variants with the same discursive frequency as do L1 speakers? Third, is their use of variants correlated with the same linguistic constraints observable in L1 speech? Finally, what are the independent variables influencing their learning of variants, for example: treatment of variants by immersion teachers and authors of French language arts materials used in immersion programs; interactions with L1 speakers; influence of the students’ L1(s); influence of intra‐systemic factors – markedness of variants; and influence of the students’ social characteristics – social standing, sex?
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".