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Record W4231982084 · doi:10.46863/ecocene.32

Speaking for the Earth and Humans In the "Age of Consequences"

2020· article· en· W4231982084 on OpenAlexaff
Noel Castree

Bibliographic record

VenueEcocene Cappadocia Journal of Environmental Humanities Cappadocia University · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change, Adaptation, Migration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEarth (classical element)AstrobiologyHistoryPsychologyBiologyAstronomyPhysics

Abstract

fetched live from OpenAlex

The environmental humanities are suffused with a sense of urgency. As geoscientists sound the alarm about human treatment of the Earth, likewise environmental humanists seek to trigger the "conversation of humankind" that seems scarcely to be happening outside universities. This essay ponders the future of the environmental humanities, and specifically their relationship to the geosciences whose messages animate much current humanistic inquiry. It cautions against a too-hasty acceptance of the notion of a "global environmental crisis." It argues for forms of interdisciplinary work that give humanists parity-of-esteem with geoscientists. And it suggests that a modified paradigm of global environmental assessment might be a viable vehicle for greater humanistic influence in the global public sphere. Throughout, humanists must somehow balance trust in geoscience with a critical stance towards its core messages about a changing Earth system. This stance is anchored on the ground of democracy, the necessary political basis for any legitimate decisions about humanity's future on Earth. Steering the environmental humanities will be a major challenge given the need for humanists to retain academic freedom yet cooperate in order to exert influence outside the academic domain.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score0.606

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 studies0.0010.001
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 head0.099
GPT teacher head0.248
Teacher spread0.149 · 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 designQualitative
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

Citations6
Published2020
Admission routes1
Has abstractyes

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