Watching change: attuning to the tempo of decay with pumpkin, weather and young children
Bibliographic record
Abstract
This paper follows a group of young children in an early childhood education setting and their growing acquaintance with a pumpkin over a five-month period. During this time, relations were forged between the pumpkin, weather and the children, and as we observed these emerging relations, we found ourselves attuning to the change of pace this brought to thinking and learning in the centre. In turn, we came to recognize this as the work of a collaboratory. In this paper, we consider the resilience, practices and demands that arise from being in the presence of a pumpkin-weather-child collaboratory. Weathering interrupts and destabilizes routine thinking. Pumpkins weather with wind, snow, sun, critters and rain. Pumpkins also weather whims of human consumption and land management practices as they are reconfigured to meet the demands of human traditions. Children draw educators and researchers into noticing the shifts and tensions unfolding with the tempo of pumpkin decay. Working with a pumpkin-weather-child collaboratory brings opportunities to reconsider the politics and practices of tempo and change in working with children, in early childhood education settings and beyond.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".