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Record W4211192170 · doi:10.1080/02646811.2021.2012349

Canada’s carbon energy overhang

2022· article· en· W4211192170 on OpenAlexaboutno aff
Alastair R. Lucas

Bibliographic record

VenueJournal of Energy & Natural Resources Law · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsRenewable energyGreenhouse gasFossil fuelElectricityNatural resource economicsLegislationBusinessPetroleum industryGovernment (linguistics)Environmental protectionEconomyEconomicsEnvironmental sciencePolitical scienceEnvironmental engineeringWaste managementEngineering

Abstract

fetched live from OpenAlex

Canada’s historical legal framework for hydrocarbon development persists, creating a ‘carbon energy overhang’ that impedes the transition to a low-carbon economy on which Canadian governments have embarked. As a result, Canada remains a petro-state, the fourth largest global oil producer with the third largest reserves. There have been greenhouse gas emission reduction initiatives, particularly by the federal government, including a national carbon tax (that survived constitutional challenge), renewable energy initiatives, energy transition legislation establishing net zero goals, and a promised cap on oil and gas industry emissions. However, two major barriers remain, notably (1) the national economic importance of the oil and gas industry with its oil sands centrepiece, located mainly in the province of Alberta; and (2) very limited room to cut electricity generation emissions, with over 80 per cent of electricity already produced by renewables and nuclear, and a lack of interprovincial transmission interties with these renewable electricity (mainly hydro)-producing provinces that export large quantities of energy to the United States.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score0.815

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)0.0010.000

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 head0.003
GPT teacher head0.161
Teacher spread0.158 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations3
Published2022
Admission routes1
Has abstractyes

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