New Perspectives in Internal Audit Research: A Structured Literature Review
Bibliographic record
Abstract
Abstract This structured literature review adopts a multimethod and multitheoretical approach to identify current knowledge about internal audit as well as related knowledge gaps. To that end, it provides an overview of post‐Sarbanes‐Oxley Act literature, organizing it under three themes: the multiple roles of internal audit, internal audit quality (IAQ), and the practice of internal audit. Despite the volume of literature published during the period covered by this review (2005 to mid‐2017), the first two themes are still in development, while the third is emergent. We suggest research avenues to fill the following main gaps: (i) Given differing opinions about the expected or actual roles of internal audit, prior literature infers that the internal audit function has become the “jack of all trades” of governance, but does not clearly capture its actual roles. (ii) The viewpoint of external auditors has dominated IAQ research, leading to a misunderstanding of how actors with greater stakes in the practice of internal audit conceptualize and evaluate IAQ. (iii) Knowledge of the actual practice of internal audit and its accountability and ethical issues is fragmentary, therefore the literature's current picture of internal audit is far from comprehensive.
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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 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.032 | 0.025 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".