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Record W7133039542

A Duty to Minimize the Corporation's Environmental Impacts: Corporate Governance and Sustainable Development

2014· dissertation· W7133039542 on OpenAlexfundno aff
Gail E. Henderson

Bibliographic record

VenueTSpace · 2014
Typedissertation
Language
FieldBusiness, Management and Accounting
TopicBusiness Law and Ethics
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsDutyCorporate governanceShareholderEnforcementSustainable developmentScope (computer science)Profitability indexLegislationStakeholder
DOInot available

Abstract

fetched live from OpenAlex

The scale and scope of today's economic activity will impact the natural environment several generations into the future. Much of this economic activity is undertaken by corporations. The interests of future generations in the natural environment, which are not protected adequately by traditional forms of environmental regulations, require moving away from the shareholder primacy norm that currently dominates both academic writing and directors' understanding of corporate governance in North America. The nascent "responsible investing" movement may result in some changes to corporate behaviour, but it also is insufficient to protect the interests of future generations. For these reasons, a new legal duty imposed on corporate directors is proposed here. This duty should be enacted through the corporations statute in order to make clear the change in the duties of directors away from simply maximizing shareholder wealth. The duty would require the board of directors to minimize the corporation's environmental impacts. "Minimize" is defined as up to the point of causing "undue hardship" to the corporation's ability to generate a profit. The duty therefore requires directors to balance profitability and environmental sustainability. This balancing is inherent in the concept of sustainable development, and therefore asking directors to take on this task is necessary to achieve sustainable development. Although this proposal raises concerns regarding compliance, enforcement and accountability, these concerns are answerable.

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.026
Scholarly communication0.0110.007
Open science0.0010.003
Research integrity0.0150.010
Insufficient payload (model declined to judge)0.0030.001

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 head0.031
GPT teacher head0.272
Teacher spread0.241 · 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 designTheoretical or conceptual
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
Published2014
Admission routes1
Has abstractyes

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