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Record W4245058240 · doi:10.32920/ryerson.14657880

Communicated identity and corporate social responsibility: a case study of Unilever's “Sustainable Living”

2021· preprint· en· W4245058240 on OpenAlexaff
Emily MacIntosh

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Identity and Reputation
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsCorporate social responsibilityPerspective (graphical)StakeholderIdentity (music)OddsPublic relationsCorporate identityBusinessSocial identity theoryStakeholder theorySocial responsibilityMarketingSociologyPolitical scienceComputer scienceSocial groupSocial science

Abstract

fetched live from OpenAlex

The goal of this study was to assess how best practices surrounding CSR messaging are employed from the perspective of stakeholder theory. Through an analysis of Unilever’s “Sustainable Living” web content, this paper establishes how a company can blend both messages about its CSR goals and achievements to create a consistent communicated identity. This paper builds on literature that suggests that communications about CSR activities and policies must acknowledge that CSR benefits both corporations and the social good. By exploring how these two messages can be blended, this paper provides a concrete example of how both types of messaging do not need to be seen as at odds with one another but can actually strengthen each other. Keywords: Corporate social responsibility, CSR, communicated identity, stakeholder theory

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0210.008
Scholarly communication0.0050.005
Open science0.0020.007
Research integrity0.0040.003
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 head0.084
GPT teacher head0.296
Teacher spread0.212 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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