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Record W2736460381 · doi:10.22215/cria.v3i0.123

The Role of Climate Change in Armed Conflicts across the Developing World and in the Ongoing Syrian War

2016· article· en· W2736460381 on OpenAlexaffvenue
Anaïs Voski

Bibliographic record

VenueCarleton Review of International Affairs · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsCarleton University
Fundersnot available
KeywordsPoliticsClimate changeDevelopment economicsPolitical instabilityContext (archaeology)Political scienceArmed conflictPolitical economyDeveloping countryEconomic growthGeographyEconomicsLaw

Abstract

fetched live from OpenAlex

This study examines the causal relationship between warming temperatures and armed conflicts in the developing world, and specifically, in Syria. The goal is to find and establish a correlation between the two factors and to understand how their complex dimensions might be influenced by the political, economic, social and environmental context in which they take place. This has been done by examining studies from Africa and the ongoing war in Syria, where resource scarcities resulting from changing weather patterns and environmental mismanagement have contributed to current political, economic and social instability. By demonstrating the increasingly prominent role climate change plays in armed conflicts, this study highlights the security challenges of political stabilization and sustainable industrialization in weak states.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.920
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0010.000
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 head0.022
GPT teacher head0.321
Teacher spread0.300 · 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 designNot applicable
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

Citations3
Published2016
Admission routes2
Has abstractyes

Explore more

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