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Record W4328097171 · doi:10.54691/bcpbm.v40i.4387

The Carbon Tax Effect on British Columbia Economy and Carbon Emission

2023· article· en· W4328097171 on OpenAlexaffabout
Haoran Liu

Bibliographic record

VenueBCP Business & Management · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCarbon taxGreenhouse gasCarbon creditRevenueCarbon fibersTax reformNatural resource economicsGovernment (linguistics)Value-added taxColumbia universityEconomicsPublic economicsFinance

Abstract

fetched live from OpenAlex

A carbon tax is the most common carbon emission control policy widely used. British Columbia is the first Canadian province to use a carbon tax and implementing a carbon tax will impact British Columbia's environment and economy. This paper analyzes the scale of the carbon tax, energy consumption, GHG emission, and government revenue in British Columbia to evaluate the effect of the carbon tax. This paper finds that a carbon tax has no impact on dramatically reducing GHG British Columbia emissions, but it can help the government get more revenue. Although the carbon tax has little effect on reducing carbon emissions in British Columbia, the carbon emissions in British Columbia have been significantly reduced compared to other provinces. Therefore, we believe that the British Columbia carbon tax has a significant impact on controlling CO2 emissions, and the value of carbon emissions can be further controlled by increasing 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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0030.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.027
GPT teacher head0.213
Teacher spread0.187 · 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 designObservational
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

Citations1
Published2023
Admission routes2
Has abstractyes

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