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Record W4407895918 · doi:10.25071/2292-4736/40440

Nature Loves to Hide

2025· article· en· W4407895918 on OpenAlexaff
Jay A. Young

Bibliographic record

VenueUnderCurrents Journal of Critical Environmental Studies · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

While humans explore and map the subsurface environments of earth, there remain unplumbed depths of nature that cannot be so exposed. This essay argues that along with a literal sense of depth as a spatial dimension, there exists a latent depth of nature hidden to everyday perception that may nonetheless manifest in/as attentive imaginative involvement. It begins by briefly comparing the ontological assumptions of Newton and Descartes with those of Merleau-Ponty before examining how the everyday phenomenon of sunrise might be interpreted through the latter. The practice of terrapsychology is then explored as a means to deepen our engagement with(in) nature and sensitively navigate the necessary ambiguity of imaginative involvement. This latter is highlighted as a corrective to the logic of certainty and control that attempts to maintain human “progress” at the expense of more-than-human nature.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.221
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.312
Teacher spread0.301 · 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.

Study designNot applicable
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

Explore more

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