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Record W4416291656 · doi:10.29173/alr2875

The Impact of Private Climate Change Litigation and Recent Competition Act Amendments on the Canadian Energy Sector

2025· article· W4416291656 on OpenAlexvenueaboutno aff
Matthew Huys, Paula Olexiuk, Ankita Gupta, Logan Aitken

Bibliographic record

VenueAlberta Law Review · 2025
Typearticle
Language
FieldSocial Sciences
TopicEnvironmental law and policy
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeCompetition (biology)Corporate governanceEnergy lawEnergy sectorPrivate sectorClimate FinanceEnergy (signal processing)

Abstract

fetched live from OpenAlex

This article examines the rise of private climate change litigation in Canada, focusing on efforts to hold corporations accountable for their contributions to climate change and their environmental representations. Canadian courts are increasingly engaging with climate claims, despite ongoing challenges such as a reluctance to interfere with corporate discretion. These cases draw on tort, corporate, and competition law, reflecting growing legal and regulatory pressure. As international precedent and domestic reforms converge, climate risk is becoming a material legal issue for Canadian energy companies. This article contends that as Canadian law continues to respond to climate-related issues, energy companies must proactively incorporate climate risk into their governance and operations to mitigate potential liabilities and maintain competitiveness in an increasingly climate-conscious market.

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)0.009
metaresearch head score (Gemma)0.027
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 score0.202
Threshold uncertainty score0.926

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.027
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0240.013
Scholarly communication0.0160.004
Open science0.0030.004
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0070.000

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 head0.032
GPT teacher head0.320
Teacher spread0.288 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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