Bibliographic record
Abstract
Abstract This paper examines how auditors prepare for the annual general meeting (AGM) and how they report their work to the shareholders there. Prior literature has suggested—but not explicitly studied—that the endpoint of an audit is a state of comfort between the auditor and the management and audit committee members, but also is potentially fragile. The fragility can arise from a failure to relay trust to the investor community, which may initiate or increase doubts about the financial report and/or the auditor's independence. We build the case that an AGM is an event to study how the endpoint of an audit engagement is both a state of collective comfort and a fragile state. The analysis is based on ten interviews and three workshops with auditors as well as observations at 67 AGMs. To analyze the field material, the paper draws on Goffman's idea of face‐work, which requires backstage preparations, notably with management, and a front stage performance as an independent auditor to relay trust to the shareholders. The paper details how auditors at the AGM perform as independent verifiers of the management's financial report. Although we recorded that auditors were typically successful in preventing the backstage activities from becoming visible to the shareholders, we found incidents that challenged both the auditors' and the managements' face. In analyzing these incidents, we found that auditors reinforced their image as independent to regain both their own face and the management's face. The management did not take a similar collective responsibility for the auditor's face, which implies that auditors were asymmetrically committed to the management. As a take‐away, the paper discusses how governance mechanisms backstage are linked and can surface front stage at the AGM.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".