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Record W6930863499 · doi:10.5281/zenodo.14164957

Readability of ESG Reports and Firm Performance: A Canadian Perspective

2024· article· en· W6930863499 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsReadabilityProfitability indexAgency (philosophy)Corporate governancePerspective (graphical)Obfuscation

Abstract

fetched live from OpenAlex

Abstract: Environmental, Social and Governance (ESG) reports are an essential communication outlet for firms, and as such, their readability is critical. Therefore, enhancing the readability of these reports is paramount to corporate communication effectiveness. This research explores the relationship among the readability of Canadian Companies’ ESG reports, their performance and movement in share price. Applying a quantitative method, we found that firms’ profitability impacted the readability of ESG reports; however, the readability of ESG reports did not significantly impact firms’ share prices. This research adds to impression management, particularly obfuscating theory, by demonstrating managerial agency about ESG reports’ readability and firms’ financial performance. Keywords: ESG Report Readability, FOG, Obfuscation Theory, Firm Performance, Firm Value JEL Classification Number: O10, O44

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)0.019
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 score0.294

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.010
Science and technology studies0.0040.003
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.036
GPT teacher head0.280
Teacher spread0.244 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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