Bibliographic record
Abstract
Modern human modes of timekeeping such as the clock and calendar conceive of time as uniform and stable, attributes that can obscure the multiplicity and instability of natural temporal processes and cycles. Because of this, some ecocritics argue we must understand time itself as a form of power that renders intra- and cross-species relations in and out of sync, and ask who is given agency through our temporal depictions, who is denied it, and how we might approach time otherwise (e.g. Nixon; Haraway; Huebener). With these ecological stakes in mind, this article will consider how Eric Carle’s classic The Very Hungry Caterpillar (1969) attempts cross-species temporal alignment through mapping the caterpillar’s process of becoming onto the days of the week. Attending both to the material structure of Carle’s book, which depicts the days of the week as frozen and calculable slices that are nevertheless uneven and penetrable, as well as to the cultural presuppositions implicit in the modern week itself, I outline how The Very Hungry Caterpillar highlights key problems of translating environmental processes into human modes of timekeeping. I then suggest what environmental insights The Very Hungry Caterpillar can provide for considering the unique temporalities of other-than-human beings during a period of climate upheaval.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.044 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".