Writing Post-modern Fairy Tales at Main Street School: Digital narratives and evolving transliteracies
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
ABSTRACT. At an elementary school in inner city Toronto, I am working with the principal, a kernel group of primary teachers, and the school’s technician to develop children’s digital literacies. Main Street School is dedicated to the pursuit of social equity for its population of grade K-5 students who are characterized by high multiculturalism and low income. The school achieves this goal through the promotion of digital learning. Our project experimentally writes the children of Main Street School into dynamic postmodern digital versions of traditional European fairy tales, and showcases the evolving transliteracies children are navigating in the pursuit of emergent literacy. REDACTION DE CONTES DE FEE POSTMODERNES A LA MAIN STREET SCHOOL : HISTOIRES NUMERIQUES ET LITTERATIES NOUVELLES RESUME. En collaboration avec le directeur, un groupe d’enseignants et les techniciens d’une ecole primaire de la grande ville de Toronto, je travaille au developpement des connaissances numeriques des enfants. La Main Street School se consacre a la poursuite de l’equite sociale chez ses eleves de niveau K-5 qui se distinguent par un multiculturalisme marque et de faibles revenus. L’ecole realise cet objectif en encourageant l’apprentissage numerique. A titre experimental, notre projet campe les enfants de la Main Street School dans des versions numeriques postmodernes et dynamiques de contes de fee europeens traditionnels, et montre comment les enfants de cultures differentes evoluent vers une culture emergente.
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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 | 0.001 | 0.000 |
| 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 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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