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Record W4394690951 · doi:10.1002/csr.2813

Corporate social responsibility in controversial industries: A literature review and research agenda

2024· review· en· W4394690951 on OpenAlexaff
Linda Jansen, Peggy Cunningham, Sandra Diehl, Ralf Terlutter

Bibliographic record

VenueCorporate Social Responsibility and Environmental Management · 2024
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCorporate social responsibilityExtant taxonBusinessPerspective (graphical)Process (computing)Public relationsSocial responsibilityMarketingAccountingPolitical science

Abstract

fetched live from OpenAlex

Abstract This study reviews the extant literature about corporate social responsibility (CSR) activities of companies operating in controversial industries. We analyze 88 articles guided by the overall question of how such companies integrate CSR into their business practices, which topics are addressed, and what the effects of these engagements are on various stakeholders. We use Maon et al.'s (2009) integrative framework to structure our analysis and develop a research agenda. Our review suggests that controversial companies' motivations are not altruistic, but largely market‐based and reactive. No studies indicated that firm mission or values underpinned the motivation for undertaking CSR programs. We also found that the perspective of employees was underrepresented. Moreover, a large number of the articles (44.3%) in our dataset dealt with communication‐related topics, neglecting many other areas of the CSR process.

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)0.007
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0170.019
Science and technology studies0.0010.002
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.137
GPT teacher head0.351
Teacher spread0.214 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations19
Published2024
Admission routes1
Has abstractyes

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