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Record W4317000443 · doi:10.5539/jms.v13n1p1

The Value Relevance of Repetitive Information—Is the Expected Social and Environmental Disclosure Informational?

2023· article· en· W4317000443 on OpenAlexaffvenueabout
Luania Gomez Gutiérrez

Bibliographic record

VenueJournal of Management and Sustainability · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsValuation (finance)Value (mathematics)Market valueStock marketBusinessEnterprise valueRelevance (law)EconomicsAccountingFinancial economicsGeography

Abstract

fetched live from OpenAlex

This paper analyzes the value relevance of firms’ social and environmental disclosure (SED) patterns expected by investors considering firms’ institutional contexts. Results show that the expected SED is value relevant for Chinese firms, not value relevant for Mexican and Canadian firms, and partial value relevant for Chilean, South African, and American firms. For Chinese firms, when the expected SED is isomorphic within the country, it is positively related to market value. However, the alternative expected SED is negatively related to market value. For Chilean firms, only the isomorphic social disclosure is (positively) valued by the stock market. Whereas for South African and American firms, only the alternative social disclosure is positively related to market value. Results suggest that institutions are essential to SED valuation as they determine whether and how stock markets value SED. Researchers in the discipline of accounting has taken an interest in social and environmental activities along with the rise of environmental protection regulations.

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)0.003
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.207
Teacher spread0.202 · 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 designObservational
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
Published2023
Admission routes3
Has abstractyes

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