A Research Note on the Influence of Outcome Knowledge on Audit Partners' Judgments
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
Audit partners may be called upon to evaluate, ex post, the work of another auditor. One example of such an evaluation is a Peer Review. An experiment was conducted that examined the influence of outcome knowledge on the going concern and peer evaluation judgments of 122 audit partners from Canada and the United States. Outcome information was manipulated at three levels—no outcome, negative outcome, and positive outcome information. The results confirm previous research and show that audit partners are subject to the influence of outcome information. Negative outcome information influenced (1) audit partners' assessments of the likelihood of the client's continued existence (hindsight effects), (2) the evaluation of the incumbent auditor's judgment (outcome effects), and (3) judgments of the importance of evidence items. Auditors who received outcome information tended to rate outcome-consistent items of evidence as more important. This suggests that the biasing effect of outcome knowledge operates by acting as a filter that magnifies the relative salience of outcome-consistent information.
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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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