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Record W1795428166 · doi:10.21083/surg.v7i2.2894

How wind turbines are not generating green energy: An economic review of the Ontario Green Energy and Green Economy Act

2014· article· en· W1795428166 on OpenAlexaffvenueabout
Nathaniel Whittingham

Bibliographic record

VenueSURG Journal · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsRenewable energyFossil fuelWind powerNatural resource economicsElectricityLow-carbon economyGreenhouse gasInefficiencyBusinessEconomyEconomicsWaste managementEngineeringMarket economy

Abstract

fetched live from OpenAlex

The Ontario Government passed the Ontario Green Energy and Green Economy Act in 2009. The Act promoted wind turbines and solar panels as a major component of the energy supply for the Province of Ontario as a replacement for coal-fired electricity generation plants. This article provides an economic assessment of the rationales that were offered for this policy, specifically, that the Act would help the Government of Ontario reduce the province’s reliance on fossil fuels, reduce carbon emissions, and stimulate the economy through the creation of jobs. The effects of the policy on the cost of electricity in the province are also considered. The analysis concludes that the Act will not reduce the Province of Ontario’s reliance on fossil fuels due to the inefficiency and unpredictability of wind turbines, ultimately leading to the need to use energy from more readily available sources of electricity such as gas. The need for fossil fuel backup also limits the potential to reduce the green house gas emissions.
 
 Keywords: Ontario Green Energy and Green Economy Act (2009); renewable energy; economic review

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.941
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.061
GPT teacher head0.222
Teacher spread0.161 · 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.

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

Citations0
Published2014
Admission routes3
Has abstractyes

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