Mythmaking in audit regulation: the Canadian initiative on ‘enhancing audit quality’
Bibliographic record
Abstract
Although extant literature has provided accounts of regulatory processes that failed to produce new or improved regulation, we know less about how regulators attempt to devise an 'illusion of regulatory action' to prevent their initiatives from being labelled failures and deflect public criticism.This study's focus is on the regulatory initiative in Canada in response to a global post-crisis regulatory trend seeking to address the problem of low audit quality.Despite decisive regulatory responses elsewhere, the Canadian project leaders not only concluded with weak regulation based on problematic assumptions, but they also actively pursued efforts to argue the opposite, thereby creating an illusion of a meaningful regulatory response.By reference to Barthes's work on mythmaking, we examine the relevant project documents to make sense of such arguments and claims essentially as instances of regulatory actors' mythmaking designed to diffuse criticism and garner public support.Our findings enable us to offer insights into and consider the role of regulatory myths as important elements in the discursive repertoires by which regulators maintain their legitimacy and authority.We also discuss certain conjectures which increase the likelihood of regulatory mythmaking.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".