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Record W2943970297 · doi:10.46743/1082-7307/2019.1459

Environmental Insecurity: Another Case for Concept Change

2019· article· en· W2943970297 on OpenAlexaff
Lee‐Anne Broadhead

Bibliographic record

VenuePeace and Conflict Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsCape Breton University
Fundersnot available
KeywordsPolitical scienceEnvironmental degradationPolitical economyEnvironmental ethicsPoliticsArgument (complex analysis)Status quoSovereigntyVulnerability (computing)ScarcityClimate changeDevelopment economicsSociologyLawEconomicsEcology

Abstract

fetched live from OpenAlex

For decades, scholars and policy-makers have disputed whether environmental degradation caused by human-induced climate change needs to be addressed and reversed in order to prevent conflict, or whether the instabilities generated by such degradation (resource scarcity, reduction of arable land, mass migration of so-called environmental refugees, etc.) provides a compelling new rationale for preparing militarily to fight the "climate change conflicts" of the future. Exploring the tension between these perspectives, the paper argues that any effective practical response implies and requires a change in the conceptual climate of the debate sufficient to discredit a literally devastating circular argument: that environmental problems, caused in part by the multiple impacts of industrial militarism, can be adequately addressed by new military strategies and spending, a "war reflex" only serving to exacerbate political tensions, widen and deepen already chronic inequalities, and inflict further ecological harm. The paper contrasts the state-centric status quo with the human-centric agenda of sustainable peace, a concept with the potential – if defined with sufficiently radical, transnational rigor – to disrupt and transform the sovereignty paradigm. The paper concludes by drawing on both Western and Indigenous political theory to ask what we think we mean by – or have come to accept as – "peace" and "power."

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.082
GPT teacher head0.327
Teacher spread0.244 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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