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Record W4391944216 · doi:10.1111/1911-3838.12356

Green Accolades and Oil‐Soaked Mermaids: A Sociology of Worth Perspective on BP's Sustainability Reporting and the Deepwater Horizon Disaster*

2024· article· en· W4391944216 on OpenAlexaffvenue
Oluwasegun Popoola, Esther R. Maier

Bibliographic record

VenueAccounting Perspectives · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsDeepwater horizonPerspective (graphical)SustainabilityHorizonOil spillSociologyBusinessPetroleum engineeringEngineeringComputer sciencePhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

ABSTRACT Sustainability reporting was originally intended to improve accountability by providing more transparency around the ecological impact of organizational action. However, as sustainability reports are increasingly used as a tool for legitimacy and a source of information by financial stakeholders, environmental concerns are being framed in economic terms. This paper draws on Boltanski and Thévenot's (2006, On Justification: Economies of Worth , Princeton University Press) sociology of worth framework to explore how the prioritization of market values facilitates the disconnect between sustainability reporting and the environment. We use the Deepwater Horizon disaster as an extreme case to illustrate how the one‐sided “compromises” with market values subjugate the values associated with social and environmental stewardship. We suggest that the integration of different conceptions of the common good can provide a more nuanced understanding of the relations between economic and environmental values.

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)0.004
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.289
Teacher spread0.273 · 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.

Study designTheoretical or conceptual
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

Citations1
Published2024
Admission routes2
Has abstractyes

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