Canadian-born trilingual children’s narrative skills in their heritage language and Canada’s official languages
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines the narrative production of 12 trilingual children aged 8;7–11;10 in three languages: heritage Romanian as a first language, mainstream English as a second, and school French as a third. Narrative macrostructure was analyzed via the Narrative Structure Scheme, while microstructure was assessed via story length, lexical diversity, and subordination index. An additional microstructural measure was Guiraud’s index of lexical richness. Results were only partially compatible with monolingual or bilingual findings. Analyses demonstrated that: (i) group macrostructural strength was equal across languages but only as a central tendency; and (ii) while the correlation between Romanian and English macrostructure almost achieved significance, neither was related to French scores. Contrary to the findings of Heilmann et al.’s monolingual study, no microstructural component correlated with macrostructure. Within microstructure, there was no significant difference in sentence complexity (measured through the subordination index) across languages, but scores for lexical diversity and Guiraud’s index were lower in French than in Romanian and English. The findings point to distinctions between trilinguals and both bilinguals and monolinguals, and the possible problem with testing trilinguals for language proficiency or disorders using instruments created for monolinguals.Trial registration: Netherlands National Trial Register identifier: ntr-.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it