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Record W4411047682 · doi:10.1017/9781009569439

Rebel Governance in the Age of Climate Change

2025· book· en· W4411047682 on OpenAlexaff
Kathleen Gallagher Cunningham, Leonardo Gentil Fernandes, Elisabeth Gilmore, Reyko Huang, Danielle F. Jung, Cyanne E. Loyle

Bibliographic record

VenueCambridge University Press eBooks · 2025
Typebook
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsCarleton University
Fundersnot available
KeywordsCorporate governanceClimate changePolitical scienceGeographyBusinessGeologyOceanography

Abstract

fetched live from OpenAlex

In many areas experiencing severe impacts from climate change, it is not the state, but rather rebel groups who wield authority over populations.Rebels are often engaged in responding and adapting to the risks and impacts of climate change as part of their local governance efforts; however, a systematic consideration of the activities and implications has been lacking.This Element looks at a set of behaviors we call "rebel environmental governance" (REG+).This refers to rebel actions aimed at protecting or managing the natural environment to affect civilian welfare amidst increasing pressures of climate change.A framework is advanced for understanding why rebels engage in environmental governance and the implications for security and climate governance.The Element brings rebel organizations into the conversation on climate change, highlighting their role in areas where state power is contested, weak, or absent.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.963
Threshold uncertainty score0.856

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 studies0.0000.001
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 head0.030
GPT teacher head0.234
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations4
Published2025
Admission routes1
Has abstractyes

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