Grammatical gender-marking ability of multilingual children in French immersion
Bibliographic record
Abstract
Aims and objectives/purpose/research questions: We explored the advantage of bilingualism and the effect of linguistic proximity on the acquisition of determiner-noun agreement, an aspect of inflectional morphology, in a French immersion setting. To our knowledge, third language acquisition literature has yet to provide evidence of a bilingual advantage in learning a particular feature of morphology in an additional language among young children. Design/methodology/approach: We compared accuracy in determiner-noun agreement on a narrative task in three groups of grade 1 and 2 students ( n = 15 in each group): a group of third language French learners whose first language marked gender, a group of third language French learners whose first language did not mark gender, and a group of English learners learning French as a second language. Data and analysis: If the determiner and the noun agreed in gender, gender on the determiner was considered correct. A repeated measures factorial ANCOVA was carried out to compare the performance among the three language groups on the proportion of correctly marked masculine and feminine nouns. Findings/conclusions: All of the children achieved high levels of accuracy on masculine nouns with no difference among the three language groups on the proportion of correctly marked masculine nouns. There was a significant difference in the proportion of correctly marked feminine nouns in favour of the group whose first language marks gender compared to the other two groups. Originality: The current study supports transfer in the domain of morphology among primary-school-aged children (who are first language speakers of diverse minority languages) in the early stages of third-language French acquisition. Significance/implications: This finding provides preliminary evidence of a bilingual advantage in the domain of morphology among young, emergent trilinguals whose first language and third language share gender marking as a linguistic feature, supporting the linguistic proximity model.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".