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Record W2169192787 · doi:10.1162/glep_a_00310

International Carbon Trade and Domestic Climate Politics

2015· article· en· W2169192787 on OpenAlexaff
Kathryn Harrison

Bibliographic record

VenueGlobal Environmental Politics · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsSocial Sciences and Humanities Research Council
Fundersnot available
KeywordsGreenhouse gasFossil fuelNatural resource economicsPoliticsInternational tradeConsumption (sociology)Supply chainBusinessClimate change mitigationEconomicsPolitical scienceWaste managementEcologyLaw

Abstract

fetched live from OpenAlex

This article theorizes about the implications for domestic climate politics of three distinct roles countries play in the global carbon supply chain: fossil fuel producer, manufacturer of carbon-intensive goods, and final consumer. Because international responsibility is assigned to territorial emissions, countries at either end of the global supply chain effectively evade environmental responsibility by shifting fossil fuel combustion to manufacturing countries. In so doing, they lessen the political challenges of reducing domestic emissions. Although exporters of carbon-intensive goods are reluctant to disadvantage local producers, importers can craft policies that both reduce territorial emissions and create local jobs. Ironically, fossil fuel exporters can emerge as leaders in reducing their own territorial emissions, a finding illustrated by case studies of British Columbia and Norway. The conclusion argues that shifting responsibility for carbon emissions to the point of either final consumption or fossil fuel extraction could facilitate an international climate agreement.

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)0.001
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: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.008
Scholarly communication0.0050.003
Open science0.0000.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.000

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 head0.009
GPT teacher head0.250
Teacher spread0.241 · 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

Citations37
Published2015
Admission routes1
Has abstractyes

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