On the use of framing strategies by the Big Four accounting firms: bringing sustainability risks into the mainstream
Bibliographic record
Abstract
This paper analyses the discourse that the Big Four accounting firms have promoted on the notion of sustainability risks, ultimately framing them as economical, technical, tractable and controllable. Drawing on Douglas and Wildavsky’s (1982 Douglas, M., & Wildavsky, A. (1982). Risk and culture: An essay on the selection of technical and environmental dangers. University of California Press. [Google Scholar]) anthropological understanding regarding the construction of risk in modern society in combination with frame theory, we study how the Big Four's specialized publications frame sustainability risks and the magnitude of their consequences. Our analysis indicates that four framing strategies characterize the firms’ discourse: representing the Big Four as proactive knowledge producers; promoting quantification and measurability; fostering neoliberal policy-making and de-emotionalizing socio-environmental issues. We maintain that through these framing strategies, the wicked issues of sustainability are overly simplified, transposed into the conventional area of organizational economics, and therefore made manageable in the unbroken pursuit of corporate growth. In other words, the apparent aim is to take sustainability risks into a territory where corporate elites are in the habit of thinking and acting: the economic arena, as delimited by the boundaries of the organization. In so doing, the Big Four create a space for their role as business advisors, ensuring that their profitability is strengthened as companies seek professional help in establishing a meaningful control structure around (narrowly defined) sustainability risks. Instead of bringing sustainability risks into the purview of organizational controllability, we believe there is a crucial need to bring business organizations and the Big Four accounting firms into the purview of responsibility toward the planet.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.045 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.014 | 0.051 |
| Scholarly communication | 0.021 | 0.020 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".