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Record W3129095351 · doi:10.22495/cgsrv5i1p5

Sustainability reporting and strategic legitimacy: The influence of operating in emerging economies on the level of GRI reporting in Canada’s largest companies

2021· article· en· W3129095351 on OpenAlexafffundabout
Philip R. Walsh, Ranjita M. Singh, Matthew Malinsky

Bibliographic record

VenueCorporate Governance and Sustainability Review · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsToronto Metropolitan University
FundersRyerson University
KeywordsSustainability reportingSustainabilityEmerging marketsBusinessLegitimacyAccountingInternationalizationCorporate sustainabilityAsset (computer security)FinancePolitical scienceInternational trade

Abstract

fetched live from OpenAlex

Corporate sustainability reporting is a contributor to strategic legitimacy (Chelli, Durocher, & Fortin, 2018) and certain traditional corporate characteristics (size, industry vulnerability) can influence the level of sustainability reporting (Drempetic, Klein, & Zwergel, 2020). However, limited literature exists in regards to sustainability reporting by Canadian companies operating in emerging countries. Content analysis of sustainability reports examined the current use of the Global Reporting Initiative (GRI) framework. Principal component analysis (PCA) provided a sustainability reporting index (SRI) measure for each firm using factor scores. Correlations and independent-samples t-testing tested the association of the level of reporting to a firm’s size, industry, level of internationalization, and level of activity in emerging economies. A review of 234 large Canadian-based, publicly-traded companies found a total of 86 companies employed the GRI framework, and data from these companies was used in this study. Asset size and vulnerable industries had no significant association with the level of sustainability reporting contrary to prior studies. Operating in emerging economies resulted in greater levels of sustainability reporting when compared to firms that do not. This finding is consistent with the external legitimacy strategy and contributes to the limited literature in this area

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 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)0.011
metaresearch head score (Gemma)0.056
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.056
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.087
GPT teacher head0.296
Teacher spread0.209 · 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 teacher head, not a consensus.

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

Citations8
Published2021
Admission routes3
Has abstractyes

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