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Record W4375945629 · doi:10.1177/10860266231168905

No End in Sight? A Greenwash Review and Research Agenda

2023· review· en· W4375945629 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOrganization & Environment · 2023
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicEnvironmental Sustainability in Business
Canadian institutionsWestern University
FundersIvey Business School, Western UniversitySocial Sciences and Humanities Research Council of Canada
KeywordsGreenwashingCorporate governancePublic relationsKey (lock)Political scienceWork (physics)Knowledge managementBusinessCorporate social responsibilityComputer scienceEngineeringComputer security

Abstract

fetched live from OpenAlex

Greenwashing is more virulent than ever. A profusion of environmental, social, and governance and net zero commitments are becoming fraught with questionable and misleading claims. At the same time, we are no closer to solving the pressing environmental and social issues of our time. In this review, we seek to examine this shift and summarize changes in greenwash research into three key phases: (a) 1.0 Static Communication; (b) 2.0 Dynamic Management; and (c) 3.0 Narratives about the Future. We analyze current key areas of developing literature and point to numerous open questions for future research. Next, we go beyond much of the published work to examine emerging tactics and lay out a forward-looking agenda for future research. We also propose a model of Corporate Miscommunication, integrating various streams in greenwash research. In doing so, we seek to lay a pathway for greenwashing researchers to finally find that elusive "end" to greenwashing.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.011

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 head0.065
GPT teacher head0.311
Teacher spread0.245 · 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