The Storied Lives Children Play: Multimodal Approaches Using Storytelling
Bibliographic record
Abstract
This paper explores a qualitative research project that drew on the work of Vivian Gussin Paley’s (1991) storytelling curriculum, where the following concepts were explored: children’s narratives through stories told, acted, and visually represented; how children construct meaning in their world; and the empowerment of voice. The study focused on the processes and growth that a diverse junior and senior kindergarten class underwent over eight weeks. The study has important implications for pedagogy and offers an innovative approach to a storytelling curriculum that engages multimodal frameworks for early literacy learning. Presenting opportunities for children to voice their storied lives orally, in image and text, and nonverbally through acting out stories enables them to explore and connect their identity texts to self, others, and the world. By engaging in, with, and through story, children reveal the complexity of their meaning-making processes, interconnecting imaginative and real experiences. By opening up learning spaces for socially constructed experiences, children’s storied lives are made visible.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.019 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".