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Record W4366808918 · doi:10.47886/9781934874707.ch15

Freshwater Fisheries in Canada: Historical and Contemporary Perspectives on the Resources and Their Management

2023· book-chapter· en· W4366808918 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Fisheries Society eBooks · 2023
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHydropowerSmall hydroStewardship (theology)Resource (disambiguation)Government (linguistics)BusinessEnvironmental planningDownstream (manufacturing)Natural resource economicsRenewable energyEnvironmental resource managementEngineeringGeographyEnvironmental sciencePolitical scienceEconomicsPolitics

Abstract

fetched live from OpenAlex

Abstract.—Canada is one of the world leaders in hydropower generation due to its vast aquatic resources and long generation history. While hydropower is considered a relatively clean and efficient renewable resource, it is not without its negative effects, and those on fish and fish habitat are generally considered among the most serious. This chapter discusses the history and current state of hydropower generation in Canada, including a breakdown by province of small and large hydropower generation capacity and proportion of total electricity generation provided by hydropower. A brief but comprehensive review is provided of the known effects of Canadian hydropower on fish and fish habitat as well as how those effects are minimized through mitigation strategies. This review is separated into three categories: downstream effects, upstream (reservoir) effects, and fish passage concerns. Resource management strategies are outlined, including how government, industry, and academia are working together to better understand and minimize the negative consequences, fill in research gaps, and meet evolving regulatory requirements. The future of hydropower section covers emerging technologies (e.g., very low head dams, hydrokinetic turbines, new fish passage techniques), key factors driving ongoing development and innovation in the hydropower industry in Canada, and ongoing environmental concerns that will be the focus of upcoming research initiatives. The investment many sectors place in the development and stewardship of hydropower in Canada keeps this country at the forefront of this industry.

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)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.570
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.017
GPT teacher head0.172
Teacher spread0.155 · 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
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
Published2023
Admission routes1
Has abstractyes

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