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Record W2782399383 · doi:10.1080/09644016.2017.1421399

The untapped potential of preferential trade agreements for climate governance

2018· article· en· W2782399383 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

VenueEnvironmental Politics · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsClimate governanceKyoto ProtocolGreenhouse gasCorporate governancePosition (finance)International tradeLegalizationClimate changeClimate policyBusinessInternational economicsEconomicsNatural resource economicsPolitical scienceEcologyBiologyLaw

Abstract

fetched live from OpenAlex

The regulatory contribution that preferential trade agreements (PTAs) make to global climate governance is assessed through an analysis of climate-related provisions found in 688 PTAs signed between 1947 and 2016. Provisions are analyzed along four dimensions: innovation, legalization, replication, and distribution. Innovative climate provisions are found in several PTAs that are in some cases more specific and enforceable than the Kyoto Protocol and the Paris Agreement. Nonetheless, these climate provisions offer limited progress because they remain weakly ‘legalized’, fail to replicate broadly in the global trade system, and were not adopted by the largest greenhouse gas emitters. Despite the inclusion of innovative climate provisions in a number of PTAs, their poor design and weak replication position them as some of the weakest environmental provisions within PTAs.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.605

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 head0.036
GPT teacher head0.225
Teacher spread0.190 · 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