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Record W4389619397 · doi:10.1080/20511817.2023.2280321

Confronting climate crisis through corporate narratives: the fairy tale in LVMH’s 2020 and 2021 social and environmental responsibility reports

2023· article· en· W4389619397 on OpenAlexaff
Annamma Joy, Joanne Roberts, Bianca Grohmann, Camilo Peña

Bibliographic record

VenueLuxury · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicMedia Influence and Health
Canadian institutionsConcordia UniversityUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsNarrativeContext (archaeology)StakeholderCorporate social responsibilityCorporationPublic relationsSituatedCrisis communicationNarrative inquiryCorporate governancePolitical scienceSociologyBusinessHistoryLiteratureLawFinance

Abstract

fetched live from OpenAlex

Situated in the context of the climate crisis this research examines the LVMH Corporation’s 2020 and 2021 Social and Environmental Responsibility Reports through the lens of the narrative structure found in fairy tales. Central characters and the trajectory of the narrative are consistent with this literary form, and counter narratives that provide context to the corporate narrative also emerge. This analysis suggests the significance of narratives to corporate communications, their application extending beyond the brand communication or user-generated content generally investigated in the marketing and consumer research literature. Moreover, the article elaborates on how luxury corporations, like LVMH, communicate their efforts to counter climate crisis in ways that meet the expectations of stakeholders, especially investors and consumers. The findings have implications for future research on how narratives impact stakeholder perceptions of luxury corporations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.175
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.286
Teacher spread0.224 · 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 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

Citations3
Published2023
Admission routes1
Has abstractyes

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