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Record W4403084595 · doi:10.1504/ijbge.2024.141802

Corporate social responsibility, allegation of corruption, and media sentiment

2024· article· en· W4403084595 on OpenAlexaff
Suresh Kalagnanam, Abhilash Nair

Bibliographic record

VenueInternational Journal of Business Governance and Ethics · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCorruption and Economic Development
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAllegationLanguage changeSocial mediaCorporate social responsibilitySentiment analysisCriminologyPolitical sciencePsychologyPublic relationsLinguisticsNatural language processingComputer scienceLaw

Abstract

fetched live from OpenAlex

This study examines the two possible effects of CSR on reputation - the insurance like effect and the boomerang effect - within the context of a uniform integrity-questioning negative event through the eyes of the media. Accordingly, we tested whether prior CSR engagement prompts media to give the firm the benefit of doubt when it is accused of 'grand corruption'. We estimated media sentiment using textual analysis on 45,000 media reports covering firms allegedly involved in 'grand corruption'. The study's findings provide no evidence of CSR providing insurance like effect, particularly in the context of integrity-based negative events. In contrast, our results appear to support the idea of the boomerang effect or a punishment for irresponsible behaviour.

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)0.002
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 score0.696
Threshold uncertainty score0.216

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.087
GPT teacher head0.358
Teacher spread0.270 · 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.

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 routes1
Has abstractyes

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