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Record W4407996973 · doi:10.3366/ircl.2025.0601

A Very Hungry Week: Challenges of Timekeeping in the Anthropocene

2025· article· en· W4407996973 on OpenAlexaff
Charis St. Pierre

Bibliographic record

VenueInternational Research in Children s Literature · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAnthropoceneEnvironmental ethicsPhilosophy

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.203

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.329
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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