MétaCan
Menu
Back to cohort
Record W4283377678 · doi:10.1080/09644016.2022.2090388

Climate action and populism of the left in Ecuador

2022· article· en· W4283377678 on OpenAlexaff
Teresa Kramarz, Donald Kingsbury

Bibliographic record

VenueEnvironmental Politics · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicEnergy and Environment Impacts
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPopulismLatin AmericansPolitical economyPoliticsAction (physics)PopulationNegotiationPower (physics)Space (punctuation)Political scienceDevelopment economicsEconomicsSociologyLaw

Abstract

fetched live from OpenAlex

There is little reason to expect developing countries to take costly local actions for global climate benefits. This is less so when populist governments of the left – who claim to speak for the poorest sectors of the population – must negotiate environmental protection and development. This article examines climate action in Ecuador, one of the poorest countries of Latin America, during a populist moment. We propose an analytical framework that explains how moments of institutional rupture create space to articulate ideational and material interests towards climate action. We explore this by analyzing an initiative that would have left oil underground in exchange for compensation by the international community. Beyond the rise of significant personalities, populist moments signal a rupture where power relations, norms, and development trajectories can be reconfigured. Populists are political entrepreneurs who articulate these conditions for personal gain, but populist moments also reveal space for climate action.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.009
Scholarly communication0.0040.002
Open science0.0000.005
Research integrity0.0010.002
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 head0.008
GPT teacher head0.204
Teacher spread0.195 · 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 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

Citations4
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental PoliticsSame topicEnergy and Environment ImpactsFrench-language works237,207