Bibliographic record
Abstract
This article uses a comic program to graphically summarize a collaborative action research project that brings together York University researchers and elementary school teachers at Joyce Public School in northwest Toronto to experimentally develop multiliteracies pedagogies in a context of emergent literacy education. The project, which has been continuously developing since 2003, searches for ways of socializing both children and teachers into new literacies in the primary and junior grades from a grassroots perspective that operates within the constraints of the modern political machinery that organizes formal education. The teacher-researchers who work in this community of practice carve out preferred trajectories for new literacies action research through narrative projects, focusing on perspectives such as playing with the myriad junctures between and across alphabetic page and iconic screen; creating dynamic textual representations; including community languages towards globally focused linguistic learning; and creating multiple representations of a narrative thread across language, genre, and culture. We work collaboratively to bridge theory and practice using a blended model that includes regular face-to-face workshops. Now an online workspace, and in its seventh year of consecutive funding, the project is moving into ludic approaches to multimodal literacy education through gaming.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".