Multispecies wit(h)nessing with children and animals: Living and dying well together
Bibliographic record
Abstract
The contours of human and more-than-human co-existence are of mutual concern in the context of global waste crises, opening to questions for early childhood environmental education on living and dying well together grounded in relational ethics. This paper attends to how and why the lifeworlds of children and animals intersect in waste landscapes as a testament to the multiscalar complexity of human and non-human entanglement in global waste flows. Louise Boscacci’s word-concept wit(h)nessing is a starting point for rethinking children’s relations with life and death in the Anthropocene, attuning early childhood pedagogies toward living and dying well with non-human others in waste landscapes. Taking waste as one of the urgent anthropogenic crises impacting childhood in the twenty-first century, this paper explores children’s fleeting encounters with multispecies life and death in a former landfill as moments for uncertain, frictional, and indeterminate pedagogical experimentation with the dispositions required to craft alternative futures.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.031 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".