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Record W3128708985 · doi:10.4236/jss.2021.91033

Ontario’s Green Energy Policy vs. Social Justice

2021· article· en· W3128708985 on OpenAlexaboutno aff
Alan Whiteley, Anne Dumbrille

Bibliographic record

VenueOpen Journal of Social Sciences · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Economic JusticeStatuteLegitimacyHarmWind powerUnintended consequencesPolitical scienceBusinessPosition (finance)LawEngineeringPublic relationsPublic administrationFinance

Abstract

fetched live from OpenAlex

Objectives: To explore the development and implementation of Ontario’s Green Energy Act and the outcomes on social justice and risk of harm to Ontario residents. To provide examples of government actions taken to achieve its goals and the occurrence of consequences, whether intended or unintended. Methods: In Ontario, many legal cases have been filed due to concern regarding the impact of industrial wind turbines on people and the environment. The contents of this article have primarily been taken from the documents filed during an Application for a Judicial Review that examined the process of approval of industrial wind turbines in Ontario. References to support the content of this article also include: evidence derived from other legal cases, government communications including records obtained by Freedom of Information requests, peer reviewed literature, and other sources. Results: Evidence is presented that suggests the government erred by creating an inflexible policy/statute that ensured that industrial wind turbines would be approved, erected and become operational at any cost. It provides examples of government actions taken to achieve this position that are contrary to widely held fundamental principles of administrative law and governmental legitimacy. Recommendations are provided for mitigating some of the outcomes of a government policy and preventing impacts on social justice from happening again.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.846
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0050.001
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.374
Teacher spread0.324 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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