The consequences of expanded audit reports for small and risky companies
Bibliographic record
Abstract
Abstract The United Kingdom mandated expanded audit reports in two waves, starting in 2013 and 2017, respectively. Prior studies of the first wave, which included large and highly regulated companies, concluded that expanded reports have limited incremental value. We focus on the second wave, which included companies listed on the Alternative Investment Market (AIM). The AIM is characterized by emerging companies that are smaller, riskier, and subject to lighter regulatory requirements and to private monitoring. We examine whether investors and other stakeholders benefit from expanded reports in this setting. We document that AIM companies have shorter expanded reports and fewer key audit matters. Next, we demonstrate that these reports have negligible incremental information value for investors or consequences for the quality and cost of audits. Finally, although we find that some variations in the expanded reports' content are associated with investor reactions to the annual report and with audit fees, variations in external monitoring and company size do not play an incremental role. By focusing on a set of companies with weaker information environments, our findings help to extend the conclusions from prior studies about the limited incremental value of expanded reports.
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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 | 0.021 | 0.176 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".