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Record W2119271266 · doi:10.1177/0270467602022004001

Globalization and Sustainability: Conflict or Convergence?

2002· article· en· W2119271266 on OpenAlexaff
William E. Rees

Bibliographic record

VenueBulletin of Science Technology & Society · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Ecological Systems Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnvironmental ethicsDestiny (ISS module)HumanitySustainabilityMythologyGlobalizationAnthropoceneValue (mathematics)Convergence (economics)SociologyIntrinsic value (animal ethics)Political scienceEcologyLawEconomicsEconomic growthHistoryBiologyPhilosophy

Abstract

fetched live from OpenAlex

Unsustainability is an old problem - human societies have collapsed with disturbing regularity throughout history. I argue that a genetic predisposition for unsustainability is encoded in certain human physiological, social and behavioral traits that once conferred survival value but are now maladaptive. A uniquely human capacity - indeed, necessity - for elaborate cultural myth-making reinforces these negative biological tendencies. Our contemporary, increasingly global myth, promotes a vision of world development centered on unlimited economic expansion fuelled by more liberalized trade. This myth is not only failing on its own terms but places humanity on a collision course with biophysical reality - our ecological footprint already exceeds the human carrying capacity of Earth. Sustainability requires that we acknowledge the primitive origins of human ecological dys-function and seize conscious control of our collective destiny. The final triumph of enlightened reason and mutual compassion over scripted determinism would herald a whole new phase in human evolution.

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)0.012
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 score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.005
Science and technology studies0.0030.024
Scholarly communication0.0170.020
Open science0.0010.012
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.011
GPT teacher head0.232
Teacher spread0.221 · 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

Citations121
Published2002
Admission routes1
Has abstractyes

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Same venueBulletin of Science Technology & SocietySame topicSustainability and Ecological Systems AnalysisFrench-language works237,207