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Wind Power in Canada

2015· book-chapter· en· W3105299604 on OpenAlexaboutno aff
Scott Victor Valentine

Bibliographic record

VenueOxford University Press eBooks · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWind powerExploitPoliticsNinthSovereigntyGreenhouse gasPolitical sciencePower (physics)Order (exchange)GeographyEngineeringBusinessLawComputer securityComputer scienceEcology

Abstract

fetched live from OpenAlex

In August 2007, the ice sheets choking off Canada’s Northwest Passage receded, permitting passage without the aid of an icebreaker for the first time in Canada’s 150-year history. Although this development presents economic opportunities, it also exposes enormous ecological threats that, 50 years ago, former Prime Minister Pierre Trudeau professed Canada should strive to avoid. Lamentably, Canada has played a role in this environmentally invidious development due to the greenhouse gas (GHG) emissions it has produced in prolific quantities over the course of its comparatively short history. This chapter highlights the barriers to developing a cohesive national energy strategy in a federal system where the states—or in Canada’s case, the provinces—enjoy constitutional sovereignty over electricity generation. More than any other case study covered in this book, this study on Canada demonstrates how political institutions can produce conditions that make it difficult to fully exploit wind power potential, despite public support for such an outcome. As of the end of 2012, Canada boasts the ninth highest amount of installed wind power capacity in the world. Based on this statistic alone, it is tempting to conclude that Canada’s wind power development policies merit recognition for being comparatively successful. However, in order to equitably assess performance in stimulating wind power development, one must also take into consideration the contextual factors which influence wind power development potential. When one does so, it becomes apparent that when it comes to wind power, Canada is a Ferrari in a world dominated by Fords. Three factors, in particular, bestow Canada with an astonishing high degree of realizable wind power potential. First, although geographically Canada is the world’s second-largest nation, it enjoys one of the lowest population density ratios in the world demand. The strategic benefit of Canada’s sheer size is that wind farms could be geographically dispersed to significantly attenuate the threats posed by wind intermittency. Wind conditions are impacted by disparate atmospheric conditions as one traverses the nearly 6,000 km from Canada’s east coast to west coast.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.045
Threshold uncertainty score0.325

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0120.001
Scholarly communication0.0050.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0340.003

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 head0.040
GPT teacher head0.241
Teacher spread0.201 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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