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Record W6922385868 · doi:10.11575/prism/35887

Potential For Expansion Of The Canadian Wind Energy Industry

2013· other· en· W6922385868 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2013
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWind powerIncentiveOpposition (politics)Investment (military)Carbon taxEnergy policyEnergy (signal processing)

Abstract

fetched live from OpenAlex

Canada has the attributes required to become a global leader in wind energy production. There are a number of forces driving the development of wind power including climate, environment, and economics. However, there are also obstacles such as public acceptance, storage, and transmission that the industry must overcome to ensure that the widespread implementation of wind energy in Canada is successful. This paper analyzes these driving forces and barriers and investigates the potential for expansion of the Canadian wind energy industry. The insights gained from this literature review are summarized into five strategic recommendations for wind energy development in Canada in the areas of economics, environment, technology, society, and policy. It is important that governments prioritize wind energy and provide incentives like feed-in-tariffs and tax breaks, to increase wind development. To account for the environmental and human health consequences of conventional fuels, a national carbon pricing mechanism is needed. This will help improve the economics of using wind power by making it more cost-competitive with cheap, polluting conventional energy sources. Increased investment into wind power technology, especially turbines, transmission infrastructure, and combined power systems (i.e. wind-hydro) will create technological improvements and increase energy efficiency. Currently, there is significant opposition to wind power in Canada, which can potentially hinder the progression of the industry. Creating bestpractice guidelines and conducting meaningful public consultation based on credible and empirical information can help to dispel many of the misperceptions about wind energy. Finally, it was determined that policy is the most important strategic area, as it is a common driver to each of the other areas and can make the biggest impact on the expansion of wind energy in Canada. A national energy policy that prioritizes wind power is an essential foundation for future development. From this, provincial and territorial energy strategies can be developed. Strong government policy support is the most important factor to Canada becoming a global leader in wind power.

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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.059
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0060.001
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.008
GPT teacher head0.176
Teacher spread0.168 · 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
Published2013
Admission routes1
Has abstractyes

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