Bibliographic record
Abstract
Storying their work with educators and young children at a Canadian early years learning centre, the co-authors puzzle over the means, affects and embodiments of digital collaboratories, proposing the latter as spaces of chimeric organic and non-organic configurations. This exploratory and experimental piece draws out opportunities for thinking complexly about the everyday encounters with the digital in early childhood education. In following the circulation of human and more-than-human digital/material events, the compositions of Franken-Tree and Franken-Sound are used to trace how common everyday interactions with digital are implicated in the enactment of pedagogical practices and, more broadly, in the making of place. Within spaces of early childhood classrooms, digital manipulations allow for multiple place-events to unravel in a non-linear enmeshing of outside and inside, of here and somewhere, of now, then and who-knows-when. Because digital enters childhood spaces with ease, educators are compelled to consider both its transgressive possibilities and disciplining powers, and to question the seemingly endless ability of algorithms to hide the layers of damage behind the layers of saturated surfaces.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.132 | 0.018 |
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".