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Record W3180404231

Do Investors Value Sustainability Reports? A Canadian Study

2012· preprint· en· W3180404231 on OpenAlexaboutno aff
Sylvie Berthelot, Michel Coulmont, Vanessa Serret

Bibliographic record

VenueRePEc: Research Papers in Economics · 2012
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityAccountingSustainability reportingStock exchangeStandardizationBusinessValue (mathematics)Voluntary disclosureCapital marketRelevance (law)Sample (material)Stock (firearms)Annual reportCorporate social responsibilityPublic relationsPolitical scienceFinanceGeography
DOInot available

Abstract

fetched live from OpenAlex

The publication of sustainability reports has increased significantly in most western countries in recent years. The fact that this type of reporting is on a voluntary basis in a number of countries raises questions about whether capital markets take these reports into account. This study attempts to address this question, drawing on a sample of Canadian companies listed on the Toronto Stock Exchange. The results suggest that investors positively value this type of reporting. These findings support the relevance of initiatives like the Global Reporting Initiative, the UN Global Compact, and that launched by the International Organization for Standardization (ISO), which focus on the development of recognized guidelines for sustainability reporting. Our findings can also serve as arguments to facilitate a firm's voluntary commitment to such types of disclosures. Copyright © 2012 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.

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)0.004
metaresearch head score (Gemma)0.020
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 score0.041
Threshold uncertainty score0.298

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0070.002
Scholarly communication0.0050.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.050
GPT teacher head0.328
Teacher spread0.278 · 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

Citations6
Published2012
Admission routes1
Has abstractyes

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