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Record W3026779393 · doi:10.1162/glep_a_00555

Shadows of Divestment: The Complications of Diverting Fossil Fuel Finance

2020· article· en· W3026779393 on OpenAlexaff
Kate J. Neville

Bibliographic record

VenueGlobal Environmental Politics · 2020
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsContinental (Canada)
Fundersnot available
KeywordsDivestmentSpillover effectEconomicsStatus quoPoliticsCommodityFinanceNatural resource economicsBusinessMarket economyPolitical scienceMacroeconomics

Abstract

fetched live from OpenAlex

This forum article offers a critical assessment of the strategy of divestment from fossil fuels as climate action, considering the unintended or spillover consequences of reinvestment in other industries. With a focus on two sectors—agriculture and renewable energy—it examines how reinvestment to achieve competitive financial returns might exacerbate non-emissions-based environmental and social damage. The analysis draws on established and emerging research in global environmental politics on the political economy of commodity trade to sound a cautionary note about divestment, arguing that the strategy can maintain the status quo as readily as it can disrupt systems of power. A focus on divestment addresses a crucial immediate problem, but without a critical look at reinvestment and the current political economic order, activists could be reinforcing the same systems of environmental and social damage they are aiming to dismantle.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.264

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 head0.011
GPT teacher head0.190
Teacher spread0.179 · 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

Citations16
Published2020
Admission routes1
Has abstractyes

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