Disclosure of Audit Activities in Annual Reports: A Comparative Study of Selected Listed Companies in Botswana and South Africa
Bibliographic record
Abstract
Audit activities form part of the key functions that enhance the reliability and validity of financial and non-financial information. One of the reporting processes investors and other stakeholders rely on when making decisions is the annual reports of enterprises which are a compilation of various reporting elements. Although internal auditors do not make direct disclosures in annual reports, many financial and non-financial disclosures are for audited items. Ultimately internally-audit activities and those of the external auditor are reflected in disclosures made by the internal audit function, the audit committee, and the external auditors themselves. The main objective of this study was to identify the levels of audit disclosure made in reference to the activities of IAFs, external auditor and the audit board committee, and to make comparisons therein between Botswana Stock Exchange (BSE) and the Johannesburg Stock Exchange (JSE) listed companies. To uncover the extent of these disclosures the current study derived seventeen (17) mandatory or voluntary audit disclosure areas that were used to conduct text analysis and to determine disclosures made for a cross-country study of three companies, each from the areas of retail, banking and insurance selected from the Botswana Stock Exchange (BSE) and the Johannesburg Stock Exchange (JSE). The study found that audit committees and internal audit functions dominated the disclosure of the audit-related variables, and that external auditors tend to confine their disclosure to areas concerned with presentation and qualification of financial statements. The study also found that companies listed in the JSE made more disclosures than their BSE counterparts, and that the retail sector made fewer disclosures as compared to the other two sectors. Furthermore, disclosures related to assessment and management risk as well as aspects of internal audit functions were the two most frequently disclosed variables in both geographic locations. The study goes on to recommend that future studies make more comparative studies by sector, geographic location, and to explore the use of a broader range of auditing variables.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".