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Record W2614755305 · doi:10.4236/jss.2017.55012

Human Health, Rights and Wind Turbine Deployment in Canada

2017· article· en· W2614755305 on OpenAlexfundaboutno aff
Carmen Krogh, Brett Horner

Bibliographic record

VenueOpen Journal of Social Sciences · 2017
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
FundersHealth CanadaGovernment of Canada
KeywordsHarmSoftware deploymentGovernment (linguistics)Right to healthHuman rightsWind powerBusinessHuman healthEconomic JusticePublic relationsPolitical scienceLawEngineeringEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

Canada has ratified international conventions which recognize the individual’s right to the enjoyment of the highest attainable standard of health. Despite the adoption of these covenants governments sometimes support policies and practises which trade off individual human health with other conflicting interests. This review evaluates the individual’s right to health against government policies and practices which support wind energy deployment in Canada. Our analysis presents government documents, peer reviewed literature, and other references which support the conclusion that wind energy deployment in Canada can be expected to result in avoidable harm to human health. This harm conflicts with contemporary health and social justice principles. Governments have a responsibility to help Canadians maintain and improve their health by generating effective responses for the prevention of avoidable harm. Individuals have a right to make informed decisions about their health. Knowledge gaps and potential risks to health should be fully disclosed. Individuals should not be exposed to industrial wind turbines without their informed consent.

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
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.099
GPT teacher head0.481
Teacher spread0.382 · 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 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

Citations2
Published2017
Admission routes2
Has abstractyes

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