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Record W2995470420 · doi:10.4324/9780429320705-4

Why ending oil and gas production in Canada is essential to a Just Transition both at home and abroad

2019· book-chapter· en· W2995470420 on OpenAlexaboutno aff
Daniel Horen Greenford

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsProduction (economics)Transition (genetics)BusinessEconomicsChemistryMacroeconomics

Abstract

fetched live from OpenAlex

This chapter focuses on what the Just Transition means for everyday Canadians as well as the world’s most marginalized groups. In countries like Canada—where a significant amount of individuals’ and the government’s income depends on oil and gas extraction—the conversation invariably ends up at jobs and revenue. Canadians have already witnessed the results of doubling down on the oil and gas sector—a decision made during the Stephen Harper administration and respected by the Trudeau administration. Oil and gas production does contribute substantially to Canada’s economy, but perhaps less than many Canadians would surmise from discourse opining the economic indispensability of the sector. Phasing down production would leave more room for Venezuelan oil to be sold abroad during the global energy transition. Fossil fuel subsidies present one of the most obvious barriers to the energy transition. Exiting fossil fuel production may be politically challenging, but the alternative is unacceptably worse.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.102
Threshold uncertainty score0.742

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 studies0.0220.010
Scholarly communication0.0090.004
Open science0.0010.002
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0120.001

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2019
Admission routes1
Has abstractyes

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