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Record W4416303738 · doi:10.1111/sena.70005

Environmental Politics in North and East Syria/Rojava: A Scoping and Conceptual Literature Review

2025· article· en· W4416303738 on OpenAlexaff
Pınar Dinç, Mo Hamza

Bibliographic record

VenueStudies in Ethnicity and Nationalism · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsUnited Nations University Institute for Water, Environment, and Health
FundersLunds Universitet
KeywordsScope (computer science)PoliticsEnvironmental justiceGeopoliticsConceptual frameworkConsciousnessEconomic JusticeDemocracy

Abstract

fetched live from OpenAlex

ABSTRACT This article presents a scoping and conceptual literature review on environmental politics in North and East Syria/Rojava. The review aims to synthesize existing academic research in English on the interplay between armed conflict and environmental change in the region, focusing on the Kurdish‐led socio‐political model known as the Autonomous Administration of North and East Syria (AANES). The study is guided by two main questions: the knowledge produced about the environment's role in AANES politics and the theoretical advances in environmental politics. Employing a scope and conceptual literature review methodology, the article identifies key themes such as ecological sustainability, gender equality and direct democracy. It highlights the challenges and opportunities faced by AANES in implementing ecological policies amidst ongoing conflict and geopolitical pressures. The findings underscore the importance of interdisciplinary approaches and the need for further research on ecological democracy, environmental justice and peace ecology. The review concludes by emphasizing the significance of radical democratic and ecological consciousness in achieving peace and justice in conflict zones.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0180.017
Science and technology studies0.0020.003
Scholarly communication0.0060.004
Open science0.0010.002
Research integrity0.0010.001
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 head0.044
GPT teacher head0.353
Teacher spread0.309 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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