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Record W2757763244 · doi:10.13135/2384-8677/2334

Rewilding Education in Troubled Times; or, Getting Back to the Wrong Post-Nature

2017· article· en· W2757763244 on OpenAlex
Michael De Danann Sitka-Sage, Helen Kopnina, Sean Blenkinsop, Laura Piersol

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Philosophy and Ethics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAnthropocentrismAnthropoceneEnvironmental ethicsPremiseIgnoranceHubrisExceptionalismSociologyEpistemologyPerspective (graphical)Political scienceLawPhilosophyPolitics

Abstract

fetched live from OpenAlex

The first part of this paper provides a series of conceptual critiques to illustrate how the recent move to inaugurate a “post-nature” world works to vindicate anthropocentric perspectives and a techno-managerial approach to the environmental crisis. We contend with this premise and suggest that troubling nature has profound implications for education. In the second part, we provide case studies from nature-based programs in The Netherlands and Canada to demonstrate how anthropocentric thinking can be reinscribed even as we work towards “sustainability.” Despite the tenacity of human hubris and the advent of the Anthropocene, we suggest these troubled times are also rich with emerging “post-anthropocentric” perspectives and practices. As such we offer “rewilding” as a means to think about education that moves beyond the romantic vestiges of “Nature” without lapsing into delusions of human exceptionalism.

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.

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 score0.250
Threshold uncertainty score0.744

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0000.001
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 head0.017
GPT teacher head0.285
Teacher spread0.268 · 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