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Record W4292298638 · doi:10.1177/03098168221114386

Whose climate intervention? Solar geoengineering, fractions of capital, and hegemonic strategy

2022· article· en· W4292298638 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCapital & Class · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Geoengineering
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsCriticismCapital (architecture)EconomicsClimate sensitivityClimate changeHegemonyCompromiseNatural resource economicsFossil fuelBusinessPolitical scienceClimate modelEngineeringGeographyLaw

Abstract

fetched live from OpenAlex

Proposals for slowing climate change by reflecting sunlight back to space, known as solar geoengineering (SG), are gaining traction in climate policy. Given SG’s capacity to slow warming without reducing carbon emissions, prominent criticism suggests that it will enable fossil fueled business-as-usual. This assessment is not without merit, yet the primary funders of SG research do not emanate from fossil capital. We analyze sources of funding for SG research globally, finding close ties to mostly US financial and technological capital as well as a number of billionaire philanthropists. These corporate sectors and associated philanthropies comprise part of ‘climate capital’ – the fraction of the capitalist class nominally aligned with climate action. We argue that SG is being positioned as a tactic for enabling incremental, market-driven decarbonization, explore key institutions advocating this approach in US climate policy, and conclude that SG is poised to serve as a tool for class compromise between fossil and climate capital.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.594
Threshold uncertainty score0.998

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)0.0030.000

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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