Supporting Indigenous children’s oral storytelling using a culturally referenced, developmentally based program
Bibliographic record
Abstract
Indigenous communities in Canada have struggled with systemic inequities that have affected education outcomes of their children. In collaboration with a Stoney Nakoda community in Western Canada, a university research team, composed of Indigenous and non-Indigenous members, offered an instruction program designed to use storytelling as a gateway to early literacy development. Indigenous researchers and collaborators guided program adaptation to increase its cultural relevance, and non-Indigenous researchers drew upon developmental research to tailor scaffolded instruction that supported increased story-structure complexity. A total of 100 children aged 5 to 7 years participated in an eight-month storytelling program, which included pre- and post-instruction assessments of storytelling and recall. After instruction, participants generated more complex, detailed stories that contained more references to their culture compared to same-age peers. They also more accurately recalled the gist of stories they were read. This study demonstrates the importance of making curricula relevant to Indigenous children by including content that is culturally relevant and developmentally appropriate.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".