Relationship between information technology auditors and auditees and their impacts on auditors
Bibliographic record
Abstract
The audit is fundamental to the reputation of the organization and to maintain its investors’ confidence, because it asserts the conformity of financial statements with good accounting practices. Therefore, information technology (IT) auditors are indispensable, since IT is pervasive. IT auditing training focuses on technical skills. However, it appears that good relationships between IT auditors and auditees are crucial to carrying out an IT audit engagement. This phenomenological study is based on interpretative phenomenological analysis. It explores what IT auditors experience, feel, and live in the context of difficult relationships and disagreements with auditees, and how this difficulty impacts these auditors, their audit engagements, and their career. The results highlight five categories of pressures on IT auditors within the scope of audit engagement. Moreover, the results indicate that the experience of the IT auditor and the support from his or her superiors are two factors which have significant influence on how the pressures are experienced. The results also suggest that the pressures experienced affect the IT auditors morally and physically and can impact the auditor’s career ambitions.
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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 | 0.012 | 0.055 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".