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Record W2901679763 · doi:10.1111/1758-5899.12586

Seeking Entry: Discursive Hooks and NGOs in Global Climate Politics

2018· article· en· W2901679763 on OpenAlexaff
Jen Iris Allan

Bibliographic record

VenueGlobal Policy · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsCarleton University
Fundersnot available
KeywordsNegotiationCivil societyPoliticsTreatyPolitical scienceClimate justicePolitical economyClimate changePublic administrationSociologyLawEcology

Abstract

fetched live from OpenAlex

Abstract Today's global climate movement is substantial and diverse. In the mid‐2000s, an influx of activists and organizations advancing social issues, such as gender, labor, justice, development and indigenous rights (to name a few) arrived at the UN climate negotiations, fragmenting civil society. I argue that, in part, the rise of these ‘new’ climate activists can be explained by the ongoing negotiations for a legally binding treaty to replace the Kyoto Protocol, which added new issues that became ‘discursive hooks’ for NGOs’ claims to belonging in the climate regime. Linking to a specific institution had two effects: it served as an entry point to frame climate issues as social issues; and it helped NGOs carve a niche in climate policy in which they were authorities. In the Paris regime, this history matters, as some NGOs will fare better under the new rules than others. First, those established in institutions enshrined in the Paris Agreement will continue to have a foothold in the regime. Second, those that built their authority on their expertise or their capacity to deliver mitigation results may find more opportunities than those making moral claims.

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)0.018
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0210.075
Scholarly communication0.0220.014
Open science0.0020.024
Research integrity0.0090.009
Insufficient payload (model declined to judge)0.0110.001

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 head0.274
Teacher spread0.266 · 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 designQualitative
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

Citations23
Published2018
Admission routes1
Has abstractyes

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