The Attitudes of Internal Auditors to Internal Audit Practice in Post-communist Countries - Case of Albania
Bibliographic record
Abstract
This paper aims to reveal the attitudes of internal auditors, towards overall internal audit practices in the post-communist country of Albania. The study presents the current state of internal audit practices in Albania from eyes of the internal auditors themselves. The study will explore the independence of the internal auditors, the level of professionalism they exhibit, the use of international standards, and whether current regulations are resulting in higher quality work in the profession. In order to study these objectives, a 169-person questionnaire was conducted, all participants where internal auditors from public and private sectors in Albania. The research findings of the study reveal that internal auditors can be assessed as independent in Albania, and that the private sector is the most independent. Regarding professionalism, internal auditors are able to detect and prevent fraud in companies. In this paper, we examine the international standards of auditing that are used by Albanian auditors; the international standards are really useful for internal auditors in Albania, even though there is much room for improvement. The number of participants was limited of 169 and analyzed one country. For the future researches questionnaire can be conducted more than one country to have comparative analysis. One improvement needed is the adaptation of the international standards in national regulations. This will make the international standards easier to apply and understand the standards in Albania.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".