MétaCan
Menu
← Back to cohort
Record W2960846791

Climate Change and Directors' Duties: Closing the Gap Between Legal Obligation and Enforcement Practice

2019· article· en· W2960846791 on OpenAlexaff
Ellie Mulholland, Sarah Barker, Cynthia A. Williams, Robert G. Eccles

Bibliographic record

VenueSSRN Electronic Journal · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsYork University
Fundersnot available
KeywordsClimate changeBusinessEnforcementGlobal warmingIncentiveClosing (real estate)Political economy of climate changePosition (finance)MainstreamFinanceAccountingPolitical scienceEconomicsMarket economy
DOInot available

Abstract

fetched live from OpenAlex

Until relatively recently, climate change was the purview of corporate social responsibility departments, to the extent it was considered at all. Siloed from finance teams, senior management and the board, it was seen as a non-financial, ethical and purely environmental matter. A public position on climate was beneficial for reputational purposes only, with conventional wisdom that climate change could not affect the financial bottom line, let alone lead to circumstances sufficient to impose personal liabilities on directors or senior management. Yet this is no longer the case. Having reached global consensus in the Paris Agreement to keep the increase in global average temperature to ‘well below’ 2°C and to pursue efforts to limit it to 1.5°C, the world’s governments and private sector leaders are taking steps to deliver the required mitigation and adaptation measures. Advances in our understanding of the potential catastrophic impacts of climate change were brought to the fore in 2018 with the special report on the impacts of global warming of 1.5°C by the Intergovernmental Panel on Climate Change. In light of these and other developments, it is now widely understood that the impacts of climate change pose foreseeable, and often material, risks to the financial performance and prospects of companies. Some of the most devastating of these impacts will be felt beyond mainstream investment and business time horizons. The extent of these impacts on future generations are dependent on the near-term actions of our current generation, which we have little incentive to fix, making climate change a ‘tragedy of the horizon’. Yet many of the risks will arise within mainstream planning and investment horizons and are already materialising today: 2017 had the highest ever costs from global weather disasters, with almost two-thirds of the US$320 billion loss uninsured. Climate change is beginning to visibly disrupt business models across a range of sectors and geographies. This paper outlines why climate change is now a core corporate governance issue. Directors now need to add a base level of climate competency to their governance skill set, as is necessary to guide their companies through the physical impacts of climate change and the transition to the net-zero emissions economy set out in the goals of the Paris Agreement. And for most, if not all, directors climate competence is not optional; governance failures and misleading disclosures relating to climate change may be actionable against individuals and companies. Focusing on key common law jurisdictions, this paper shows that existing corporate and securities laws are conceptually capable of being applied to failures to govern and disclose climate risk. While there is generally a gap between the law on the books and its enforcement against directors, this paper argues that the climate change litigation gap is likely to close in the relatively near future. This has led to the development of a number of tools to assist boards and their committees to navigate the new governance and disclosure expectations and to take up the opportunities created by climate disruption on business.

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)0.067
metaresearch head score (Gemma)0.093
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 score0.067
Threshold uncertainty score0.354

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0670.093
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0190.049
Scholarly communication0.0290.027
Open science0.0030.016
Research integrity0.0160.024
Insufficient payload (model declined to judge)0.0120.001

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 head0.027
GPT teacher head0.258
Teacher spread0.231 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueSSRN Electronic Journal→Same topicRegulation and Compliance Studies→French-language works237,207→