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Record W4410599658 · doi:10.1017/s0020818325000037

From Gridlock to Ratchet: Conditional Cooperation on Climate Change

2025· article· en· W4410599658 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Organization · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsConcordia University
FundersFonds de Recherche du Québec-Société et Culture
KeywordsGridlockPledgeCommitCollective actionClimate changePoliticsArgument (complex analysis)DeadlockPolitical sciencePolitical economy of climate changePolitical economyClimate change mitigationEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract Climate treaties have progressed over time to pledge substantial reductions in global warming. This is surprising, given that theories of climate politics emphasize collective-action problems and domestic deadlock. I first describe the process of updating climate mitigation targets under the Paris Agreement. Then I develop a theoretical argument that explains target changes based on how countries are situated in economic and political networks. Trade flows create competitive economic pressures that may undermine climate action, but these pressures may ebb when partners also commit to act. I argue that political networks support conditional cooperation, especially when institutional design promotes gradual commitments. I use spatial regression models to study how countries’ climate targets are related to their partners’ prior targets. I find that countries pledged stronger updated mitigation targets in the Glasgow Climate Pact when their closest political partners submitted strong targets in the Paris Agreement. This suggests the Paris Agreement drove conditional cooperation on mitigation.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.999

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)0.0020.004

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 head0.052
GPT teacher head0.270
Teacher spread0.218 · 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