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Record W4415475290 · doi:10.5751/es-16247-300415

The nature of peace: post-conflict peacebuilding and its implications for environment and livelihoods

2025· article· en· W4415475290 on OpenAlexvenueno aff
Fariborz Zelli, Torsten Krause

Bibliographic record

VenueEcology and Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsnot available
FundersVetenskapsrådetLunds UniversitetSvenska Forskningsrådet Formas
KeywordsPeacebuildingLivelihoodPoliticsDemocracyIndigenousDeforestation (computer science)Civil societyNational park

Abstract

fetched live from OpenAlex

This editorial introduces the special feature’s main objective: to provide latest research findings on the dynamics between environmental protection and post-conflict peacebuilding processes after internal armed conflicts. In the feature, we propose a broad understanding of environmental peacebuilding that takes all cycles of the peacebuilding process into account and puts stronger emphasis on the long-term social and environmental impacts. Based on this conceptualization, the contributions to this special feature analyze a series of environmental, social, political, and economic dimensions of post-conflict environmental peacebuilding processes in a diversity of geographical contexts. <br><br> Building on a wide mix of methods from various disciplinary angles, the feature provides the reader with a range of important and novel results: on different types of impacts on ecosystems and livelihoods (e.g., largely detrimental consequences across Uganda or for environmental human rights defenders in Colombia as a whole, but also decreasing deforestation in Colombia’s Sumapaz territory); for various timings and cycles of peacebuilding processes (e.g., ongoing violent conflicts around Virunga National Park in the Democratic Republic of Congo or Iraq’s Kurdistan region, a recent truce in Tigray in late 2022, less than a decade of peacebuilding in Colombia, and over 20 years since the peace agreement in Uganda); at different political levels (from local areas like DRC’s Virunga region or Colombia’s Sumapaz area to national politics and international law contexts); and for a large set of actors (such as local farmers, indigenous communities, civil society groups, rebel groups, and local and national governmental actors). One core overarching finding across these contributions is the dominance of nature-neglecting, instrumentalizing and extractivist narratives with their far-reaching impacts on post-conflict societies. These impacts are not only environmental, e.g., deforestation and biodiversity loss, but also social, in the form of threats to livelihoods of vulnerable communities, and they re-produce old but create also new forms of physical, structural, and cultural violence.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.010
GPT teacher head0.286
Teacher spread0.276 · 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 designObservational
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

Citations0
Published2025
Admission routes1
Has abstractyes

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