MétaCan
Menu
Back to cohort
Record W3097781576 · doi:10.1002/bse.2657

Financial materiality in the informativeness of sustainability reporting

2020· article· en· W3097781576 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 · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsUniversity of Prince Edward IslandHEC Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMateriality (auditing)AccountingBusinessCorporate governanceSustainability reportingStock (firearms)SustainabilityStock priceCorporate social responsibilityFinancePublic relations

Abstract

fetched live from OpenAlex

Abstract This study examines whether financial materiality in environmental, social, and governance (ESG) disclosure benefits the stock market by increasing the amount of accessible and relevant firm‐specific information. Based on the value relevance of information and the principle of financial materiality, we demonstrate that disclosing material ESG information increases stock price informativeness. We conduct an automated content analysis of 150,000 electronic documents filed by firms listed on the S&P/TSX Composite Index from 1999 to the end of 2014. Our findings show that ESG disclosure is indeed value relevant for investors and that financial materiality in ESG disclosure leads to more informative stock prices. In addition, the effect of ESG disclosure on stock price informativeness differs across the ESG components, being more sensitive to the social component. This study contributes to the literature on sustainability reporting, and in particular to the ongoing discussion about whether the financial materiality of ESG issues matters. This study also deepens the understanding of agency theory predictions about the economic effects of ESG disclosure.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.526
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.030
GPT teacher head0.235
Teacher spread0.205 · 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