MétaCan
Menu
Back to cohort
Record W1948920170 · doi:10.1002/bse.1840

Board Effectiveness and the Voluntary Disclosure of Climate Change Information

2014· article· en· W1948920170 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBusiness Strategy and the Environment · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversity of Ottawa
FundersUniversity of TorontoUniversité de ToulouseUniversity of Ottawa
KeywordsTransparency (behavior)Voluntary disclosureAccountingClimate changeBusinessTurnoverRelevance (law)Quality (philosophy)Public relationsPolitical scienceEconomicsManagement

Abstract

fetched live from OpenAlex

Abstract This paper examines the relationship between board of directors' effectiveness and voluntary climate change disclosures. Since risk management and reporting fall under the board's responsibility, we relate board effectiveness to the firm's decision to voluntarily respond to the Carbon Disclosure Project (CDP) annual questionnaire as well as the quality of disclosures about climate‐change‐related risks and strategies to mitigate them. Our results show a positive association between board effectiveness and the firm's decision to answer the CDP questionnaire as well as its carbon disclosure quality. The paper contributes to the ongoing debate on the determinants of voluntary climate change disclosures. Our findings highlight the importance of the board of directors' role in enhancing the transparency and relevance of voluntary disclosures of climate change business impacts. Copyright © 2014 John Wiley & Sons, Ltd and ERP Environment

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.196
Teacher spread0.186 · 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