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Record W7049095923

Motivations for Issuing Standalone CSR Reports: a Survey of Canadian Firms

2013· article· en· W7049095923 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFlorence Research (University of Florence) · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Electrical Measurement Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate social responsibilityTransparency (behavior)StakeholderCompanies ActStakeholder theoryStakeholder engagementSocial responsibilitySurvey researchCorporate governance
DOInot available

Abstract

fetched live from OpenAlex

There is a debate in the literature regarding the underlying motivations for companies who voluntarily issuing standalone CSR reports (Clarkson et al., 2011). To gain insight into this debate we report the results of a survey which asks 221 Canadian firms their motivations, their costs and whether they follow independent GRI guidelines in choosing to issue (or not issue) their CSR report. Of the 57 companies that responded to our survey, 32 issued standalone reports and 25 choose not to. The most frequently cited reason for issuing standalone CSR reports was to signal their interest in social responsibility to stakeholders followed closely by CEO/Board commitment to CSR. Other frequent responses were that companies wished to communicate to stakeholders a policy of corporate transparency and to put all CSR information in one place. Approximately 71% of companies that issue CSR reports follow GRI reporting guidelines and 25.8% of these CSR Reports are independently verified. Over 50% of companies reported that it costs over $75,000 to produce the standalone CSR report, takes over four months to prepare on average, and requires five or more people to produce it. The primary reason that companies chose not to issue CSR reports was lack of stakeholder pressure and regulatory requirement to do so. Our research provides support for the need for multiple perspectives to provide insight into standalone CSR reporting.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.651
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.096
GPT teacher head0.292
Teacher spread0.195 · 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