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Record W2102692245 · doi:10.1142/s2010007812500017

HOW LARGE ARE THE IMPACTS OF CARBON MOTIVATED BORDER TAX ADJUSTMENTS?

2009· article· en· W2102692245 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

VenueClimate Change Economics · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFiscal Policy and Economic Growth
Canadian institutionsWestern University
Fundersnot available
KeywordsCarbon taxEconomicsNatural resource economicsBusinessPublic economicsInternational economicsGreenhouse gasGeology

Abstract

fetched live from OpenAlex

This paper discusses the size of impact of carbon motivated border tax adjustments on world trade. We report numerical simulation results which suggest that impacts on welfare, trade, and emissions will likely be small. This is because proposed measures use carbon emissions in the importing country in producing goods similar to imports rather than carbon content in calculating the size of barriers. Moreover, because border adjustments involve both tariffs and export rebates, it is the differences in emissions intensity across sector rather than emissions level which matters. Where there is no difference in emissions intensities across sectors, Lerner symmetry holds for the border adjustment and no relative effects occur.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.052
GPT teacher head0.244
Teacher spread0.191 · 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