Joint Audit: Issues and Challenges for Researchers and Policy-Makers
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.
Bibliographic record
Abstract
The publication of the European Commission Green Paper, ‘Audit Policy: Lessons from the Crisis’ in October 2010, has stirred up a lively debate on the role of joint audits. This literature review identifies and evaluates, for the benefit of future research and regulators, existing evidence about joint audits. We find limited empirical support to suggest that joint audits lead to increased audit quality, but some empirical support to suggest that joint audits lead to additional costs. Overall, this paper indicates that joint audit should be seen as a mechanism that is embedded in a broader institutional context and not be considered in isolation from other factors that might impact the audit market. The results indicate that various country-level characteristics are simultaneously at play. While joint audits can potentially enhance the audit market competition by allowing smaller audit firms to maintain larger market shares, the related impact on audit quality has not yet been clearly demonstrated and thus provides a promising avenue for future research.
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 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 | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it