The Informational Value of Key Audit Matters in the Auditor's Report: Evidence from an Eye-Tracking Study
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
SYNOPSIS We examine whether and how the addition of mandatory paragraphs that highlight Key/Critical audit matters (KAMs) in the auditor's report affects users' information acquisition process using eye-tracking technology. We experimentally manipulate the presence of KAMs, their number (one or three KAMs), and their format with the inclusion of an overview of audit procedures performed to address each KAM. We find that KAMs have attention directing impact, in that participants access KAM-related disclosures more rapidly and pay relatively more attention to them when KAMs are communicated in the auditor's report. However, when exposed to an auditor's report with several KAMs, participants devote less attention to the remaining parts of the financial statements. Depending on the relevance of the information for the decision task users are less attentive to, our results have direct policy implications as they underline the potential costs and benefits associated with KAMs.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 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