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Record W1834797527

A Case Study on the Legal Impacts of Corporate Sustainability Pledges in the Alberta Oil Sands

2013· article· en· W1834797527 on OpenAlexaffvenueabout
Jeffrey Bone

Bibliographic record

VenueDalhousie journal of legal studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicProperty Rights and Legal Doctrine
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsOil sandsSustainabilityBusinessNatural resource economicsEconomicsGeographyAsphalt
DOInot available

Abstract

fetched live from OpenAlex

Suncor Energy Inc. is Canada’s largest oil and gas producer with significant operations in the Alberta oil sands. In its 2010 Sustainability Report, the corporation made several long-term environmental pledges. This paper confronts a hypothetical situation involving these environmental pledges. What if Suncor’s commitments prove to be effective from an environmental standpoint, but they become more costly from a financial perspective than Suncor anticipates? In accordance with their statutory fiduciary duties, Suncor directors have a choice to make between two options. First, the company could increase or maintain expenditures in order to meet these commitments. Second, the company could limit its projected expenditures with the consequence that environmental commitments will not be met due in part to financial constraints. This case study applies Canadian corporate statutory fiduciary duties to these alternatives and ultimately finds that such pledges do not create legal liability for directors when they fail to uphold environmental commitments. However, directors may be entitled to follow through on voluntary environmental pledges that are more costly than initially anticipated without incurring liability from disgruntled shareholders.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.910

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.075
GPT teacher head0.339
Teacher spread0.265 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2013
Admission routes3
Has abstractyes

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