The Role of the Internal Auditor in Strengthening the Governance of Economic Organizations Using the Three Lines of Defense Model
Bibliographic record
Abstract
Purpose: This paper aims to investigate the impact of the three lines of defense (TLOD) in strengthening corporate governance in industrial companies in the Sultanate of Oman. Methodology: A questionnaire was used to collect data from industrial companies in the Sultanate of Oman. A total of 300 questionnaires were distributed; for the 159 valid questionnaires used for analysis, PLS-SEM was used in the data analysis. Results: The results showed a significant impact of the three variables (commitment of operational management to legal, regulatory, and ethical requirements; risk management, compliance, and quality functions; and the role of assertive internal auditing according to the third line of defense model) in strengthening corporate governance. Practical implications: The study indicates that the TLOD model plays a more decisive role in determining the strengthening of corporate governance, and therefore, the results of the study can help industrial companies to understand the role of the TLOD model in strengthening control procedures, risk management, and governance. Originality/value: The study constitutes a management strategy that assists organizations in diagnosing the degree of corporate compliance with the TLOD and identifying weaknesses in their procedures.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".