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Record W2111267740

Sustainability and Our Cultural Myths.

2004· article· en· W2111267740 on OpenAlexvenueno aff
David Chapman

Bibliographic record

VenueCanadian journal of environmental education · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsMythologySustainabilityMeaning (existential)Environmental ethicsSociologyConsciousnessWork (physics)Environmental educationEpistemologySocial sustainabilitySocial sciencePedagogyEcologyPhilosophyEngineering
DOInot available

Abstract

fetched live from OpenAlex

This paper begins by weighing the term sustainability and considering its meaning in “common culture” terms as people outside the academy might understand it. The first implication is that none of our current behaviour meets the simplest criteria of sustainability. The question “why?” is raised. In responding to this question I suggest that our social structure is founded on a number of myths. My view is that these myths provide a useful explanation for the false consciousness in which western culture appears to be lost. I conclude that educational efforts that do not confront the system of myths work against the environment by tacitly supporting the mechanisms and structures that are the causes of environmental problems. I suggest that the U.N. decade for sustainability must be made to work despite critique of the term sustainability. In closing I suggest that confronting the myths addresses only one aspect of a concert of forces that constrain education on behalf of the environment and elaborate some suggestions for new thinking.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0090.064
Scholarly communication0.0090.008
Open science0.0010.005
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.004
GPT teacher head0.234
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations19
Published2004
Admission routes1
Has abstractyes

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