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Record W2138925822 · doi:10.5539/jsd.v2n3p3

Security and a Sustainable World

2009· article· en· W2138925822 on OpenAlexvenueno aff
Don Clifton

Bibliographic record

VenueJournal of Sustainable Development · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainable Development and Environmental Policy
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityMilitarismEcological footprintNatural resourcePoliticsArgument (complex analysis)TypologyAction (physics)Environmental ethicsEarth SummitSustainable developmentSocial sustainabilityPolitical scienceSociologyEcologyLaw

Abstract

fetched live from OpenAlex

This article explores how issues of security, conflict, violence and the military are considered in the sustainability literature. Despite these issues not being particularly well developed within the sustainability setting, various approaches are identified, critiqued, and compiled into a preliminary typology framed around reformist and transformational approaches to a sustainable world. The analysis also reveals how efforts to link military activity to concepts of economic, social, and environmental sustainability are creeping into sustainability narratives at the political level to justify continued militarism under the disguise of sustainability language. Footprint analysis is also used to support an argument that without decisive action, including a substantial reallocation of society's resources away from the military to sustainability focused initiatives, competition over natural resources is likely to intensify in the future and the long standing tradition of exploitation by the rich and powerful of the poor, future generations, and other species with humans share the planet, is likely to continue.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.020
Scholarly communication0.0100.009
Open science0.0000.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.005
GPT teacher head0.209
Teacher spread0.204 · 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

Citations12
Published2009
Admission routes1
Has abstractyes

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