Tending, counting and fitting with post-developmental fat(s) in early childhood education
Bibliographic record
Abstract
This article responds to Euro-western conceptions of childhood obesity that understand fat within developmental narratives, as biochemically consequential and as a marker of individualized responsibility. Drawing in multiple fat(s) generated in a pedagogical inquiry with early childhood educators and children, the author articulates ‘post-developmental fat(s)’ as fat(s) that trouble the logics, practices and relationships required to understand fat as obesity. She traces how situated methods of tending fat(s) generated specific possibilities for counting and fitting fat(s). Foregrounding questions of how fat(s) happen and what fat(s) can do in early childhood education, the author takes seriously how fat(s) matter momentarily amid intentional, speculative and deeply politicized pedagogical practices oriented towards doing fat(s) differently in early childhood education.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.065 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| 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".