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Record W2568502790 · doi:10.1139/cjfas-2016-0480

Authorized net losses of fish habitat demonstrate need for improved habitat protection in Canada

2017· article· en· W2568502790 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsUniversity of CalgaryFisheries and Oceans CanadaMemorial University of Newfoundland
Fundersnot available
KeywordsHabitatFisheryFish habitatHabitat destructionFish <Actinopterygii>Scope (computer science)AuthorizationBusinessFisheries managementSafe harborGovernment (linguistics)FishingEnvironmental resource managementGeographyEcologyEnvironmental scienceLawPolitical scienceBiologyComputer security

Abstract

fetched live from OpenAlex

Fish habitat is essential to the stability and productivity of fisheries. In Canada, the primary legal tool for protecting fish habitat is the federal Fisheries Act. In 2012, this law was changed to narrow the scope of habitat protection. The government’s position was that the previous regime went beyond what was necessary to protect fish and fish habitat. Here, we tested that assertion by examining Fisheries Act authorizations to harmfully alter, disrupt, or destroy fish habitat issued by Fisheries and Oceans Canada during a 6-month period in 2012, obtained using access to information processes. We found the majority of projects (67%) were authorized to impact more habitat than proponents were required to compensate for, likely resulting in a net loss of fish habitat. Our analysis show an aggregate net loss — defined as authorized impact minus required compensation — of 2 919 143 m 2 authorized across 78 projects. Drawing from these results, we present four recommendations for an improved habitat protection regime under a renewed Fisheries Act, emphasizing the need to establish a public registry for authorizations and monitoring data.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.304

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.214
Teacher spread0.190 · 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