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Record W31809434 · doi:10.29173/alr323

The Canadian Environmental Assessment Act and Global Climate Change: Rethinking Significance

2009· article· en· W31809434 on OpenAlexfundvenueaboutno aff
Toby Kruger

Bibliographic record

VenueAlberta Law Review · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
FundersGovernment of Canada
KeywordsGreenhouse gasContext (archaeology)Climate changeGovernment (linguistics)Process (computing)Environmental planningEnvironmental resource managementBusinessPolitical sciencePublic economicsEconomicsEnvironmental scienceComputer scienceGeographyEcology

Abstract

fetched live from OpenAlex

Environmental assessments conducted under the Canadian Environmental Assessment Act turn on the key finding of whether a proposed project is likely to cause significant adverse environmental effects. Despite the importance of “signifcance” in the assessment process, the lack of objective criteria to determine when the threshold of significant has been reached in the greenhouse gas emissions context has made the process ineffective. This prevents meaningful judicial review and the regulatory scheme from properly confronting climate change. The article examines how significance might be objectified under the current regulatory and government policy framework, including the possibility of establishing benchmarks, assessing relative significance by comparing the proposal to alternatives, and the use of mitigation strategies.

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)0.032
metaresearch head score (Gemma)0.052
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: Empirical · Consensus signal: none
Teacher disagreement score0.124
Threshold uncertainty score0.899

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0180.039
Scholarly communication0.0190.006
Open science0.0080.005
Research integrity0.0190.017
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.298
Teacher spread0.279 · 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
GenreEmpirical

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

Citations11
Published2009
Admission routes3
Has abstractyes

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