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Record W1853689173 · doi:10.1139/cjfas-2012-0411

The length of environmental review in Canada under the <i>Fisheries Act</i>

2013· article· en· W1853689173 on OpenAlex
Derrick T. de Kerckhove, Charles Kenneth Minns, Brian J. Shuter

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.
fundA Canadian funder is recorded on the work.
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 · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsExpeditingLegislationGovernment (linguistics)LegislatureParliamentEnvironmental impact assessmentBusinessPublic economicsPolitical scienceEnvironmental planningEnvironmental protectionPublic administrationEconomicsGeographyPoliticsLaw

Abstract

fetched live from OpenAlex

There is a common misconception among government officials that environmental regulations are bad for economic growth. Citing economic reasons, the Canadian federal government passed legislation in 2012 restricting the length of environmental reviews of new developments, even though review times were not empirically known. Using annual reports to Parliament from 2001 to 2010, we estimated using time-series analyses that review times under the Fisheries Act conformed to the new government mandated review times prior to major legislative changes to federal environmental oversight. The majority of submissions were processed within 1 year for mitigated impacts and within 2 years for authorized impacts. While it is possible that a minority of projects take longer, there is no evidence of large backlogs in the review process, and Canadian review times appear quicker than those in the United States. We highlight the need for empirical estimates of the costs of environmental regulations before governments enact substantial legislative changes that reduce environmental oversight and offer alternate recommendations for expediting environmental review times.

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 score0.257
Threshold uncertainty score0.333

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 communication0.0000.001
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 head0.020
GPT teacher head0.188
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