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A Tale of Two Climate Policies: Political Economy of British Columbia’s Carbon Tax and Clean Electricity Standard

2013· article· en· W1997693727 on OpenAlexaffvenueabout
Ekaterina Rhodes, Mark Jaccard

Bibliographic record

VenueCanadian Public Policy · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCarbon taxGreenhouse gasTonneElectricityNatural resource economicsEconomicsAgricultural economicsEconomyBusinessWaste managementEngineering

Abstract

fetched live from OpenAlex

In 2007–08, British Columbia implemented two significant climate policies: the first broadly based carbon tax and the first almost 100-percent “clean” electricity standard in North America. We describe the key design characteristics of these policies and analyse them against the criteria of greenhouse gas (GHG) emissions reductions, economic efficiency, administrative feasibility, and public acceptance. We find that the clean electricity standard is estimated to reduce four to six times more emissions per year by 2020 than the carbon tax, but at an average cost per tonne of CO2 reduced that is significantly higher than the carbon tax at its current level. Interestingly, the clean electricity standard achieves higher and steadier levels of public acceptance, which might be attributed to its lack of visibility, relative to the carbon tax.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.482

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0050.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.000

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 head0.028
GPT teacher head0.227
Teacher spread0.199 · 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 designTheoretical or conceptual
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

Citations62
Published2013
Admission routes3
Has abstractyes

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