The Determinants of Joint Audit Imbalance: A Supply-Side Analysis
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 potential benefits of joint audits for audit quality and audit market competition remain the subject of ongoing debates in Europe. Within this context, a consensus emphasizes the importance of a balanced allocation of work between the two audit firms. This raises questions about the factors that may hinder the implementation of balanced joint audits. We examine the supply-side determinants of joint-audit imbalance in the French setting. We find that mixed joint auditor pairings, involving a Big 4 and a Non Big 4, are a primary driver of imbalance, reflecting differences in reputation, technology and resources. Moreover, frequent collaboration between joint auditors and disparities in industry specialization further contribute to the imbalance. Our findings provide insights into the role of auditors’ production functions in shaping the (in)ability to achieve balanced joint audits. Consequently, requiring strictly balanced joint audits may limit the ability to involve smaller audit firms as joint auditors.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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