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Record W3186776965 · doi:10.1093/yiel/yvaa015

2. Canada

2019· article· en· W3186776965 on OpenAlexaboutno aff
Stanley D. Berger

Bibliographic record

VenueYearbook of International Environmental Law · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsRepealBankruptcyGovernment (linguistics)LegislatureBusinessPublic administrationLawFinancePolitical science

Abstract

fetched live from OpenAlex

The year 2019 saw the most significant environmental legal developments in Canada in constitutional law disputes over the regulation of the environment between the federal and provincial governments and provincial and municipal governments. The litigation centred on the federal government’s legislative initiative to meet its international climate change commitments through the restriction of carbon emissions and the resistance of some provincial governments to the federal scheme. On a second litigation front, the province of Alberta’s efforts to build the Trans Mountain pipeline extension to move more oil to the British Columbia coastline in order to serve oversea markets were temporarily stymied by the British Columbia government’s use of its provincial environmental approvals laws to limit the flow of fuel into the province. Third, the city of Victoria unsuccessfully attempted to restrict the use of plastic bags without having prior provincial approval in place. Fourth, receivers in bankruptcy were unsuccessful in using the federal bankruptcy laws to shield bankrupt estate assets from provincial regulators addressing abandoned oil wells. Finally, the newly elected Ontario government, which had campaigned during the election to dismantle the provincial cap-and-trade program, was unsuccessful in arguing that the election campaign itself could act as an effective substitute for the consultation process under the provincial Environmental Bill of Rights. The government ultimately followed the consultation process and proceeded to repeal the cap-and-trade program.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.993

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.003
GPT teacher head0.213
Teacher spread0.210 · 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
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

Citations0
Published2019
Admission routes1
Has abstractyes

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