Witnessing the Ruins: Speculative Stories of Caring for the Particular and the Peculiar
Bibliographic record
Abstract
Educational scholars and practitioners are confronting long-held anthropocentric pedagogical practices as well as notions of care. To trouble the notion of care, this article draws from the collaborative research that stories the collective experiences of children, educators, and researchers at an early years learning centre located in an emerging suburban enclave of a mid-sized city in southwestern Ontario, Canada. Our work is guided by the question of how we as educators and scholars reclaim and augment the politics of care. Through the practice of storying everyday encounters, we explore how emerging and precarious relations with more-than-human others, both real and imaginary, challenge anthropocentric notions of care.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.031 | 0.112 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.004 | 0.010 |
| 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".