Narratives by bilingual children: a tale of strengths and growth during kindergarten
Bibliographic record
Abstract
Given their significance in daily life and frequent inclusion in clinical and educational assessments, children’s narrative abilities merit investigation. The present study examines the narratives of children acquiring an additional language, adding to the more abundant studies of monolingual children. Sixty kindergartners (mean age 68 months) residing in Quebec, Canada participated. All spoke a minoritized language at home, and were being instructed in French, the majority language, at school. The children told stories in French based on pictures from the Edmonton Narrative Norms Instrument (Schneider, Dubé, and Hayward, 2005 Schneider, P., R. V. Dubé, and D. Hayward. 2005. The Edmonton Narrative Norms Instrument. https://www.ualberta.ca/communications-sciences-and-disorders/resources/clinical-supervisors/edmonton-narrative-norms-instrument/enni-in-other-languages.html. [Google Scholar]) in late fall or early winter, and again in spring. Their stories were subsequently analyzed for their macrostructural features. Despite limited exposure to French prior to kindergarten, the majority of children were able to communicate the central problem in the story, characters’ attempts to resolve the problem, and outcomes of those attempts. Furthermore, the children’s scores increased from time 1 to time 2 overall, and for four of eight story grammar elements. The higher scores were due to higher scores on elements as well as the emergence of new elements in children’s stories at time 2. The findings can help guide expectations for narrative growth among emerging bilingual children and inform instruction.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".