MétaCan
Menu
Back to cohort
Record W1998956037 · doi:10.3141/2119-03

Cap-and-Trade

2009· article· en· W1998956037 on OpenAlex
Adam Millard‐Ball

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2009
Typearticle
Languageen
FieldEnergy
TopicEnergy, Environment, and Transportation Policies
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouse gasClean Air ActAllowance (engineering)Emissions tradingRevenueEconomicsCarbon taxNatural resource economicsTonneCarbon priceEconomic impact analysisAgricultural economicsBusinessEngineeringWaste managementAir pollutionFinanceOperations managementMicroeconomics

Abstract

fetched live from OpenAlex

This paper identifies for transportation planners five key implications of extending cap-and-trade for greenhouse gas emissions to the transportation sector, as envisaged in legislative and regulatory proposals in the U.S. Congress and in the western states and Canadian provinces. First, cap-and-trade would increase gasoline prices as refiners and fuel importers pass on the cost of carbon allowances; a $30 per metric ton price of carbon allowances equates to 27 cents per gallon of gasoline. Second, transit, smart growth, and other emission reduction projects might be eligible for billions of dollars in revenue from carbon allowance auctions. Third, as emissions would be constrained at the level of the cap, transportation projects would be unlikely to have any impact on aggregate emissions. Any environmental benefit of a project (reduced emissions) would be converted into an economic benefit (reduced carbon allowance prices and thus reduced compliance costs in other sectors). Fourth, the converse of this argument suggests a weakening of the potential to use the environmental review process to mitigate emissions from development projects. There may be an economic impact (higher carbon allowance prices), but not an environmental impact (emissions would be constrained at the level of the cap). Finally, extending cap-and-trade to the transportation sector would eliminate the potential for revenue from the sale of offsets, as this would double count emission reductions.

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)0.003
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 score0.557
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.062
GPT teacher head0.357
Teacher spread0.295 · 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