Bibliographic record
Abstract
Integrated Reporting (IR) is a new concept which has been receiving considerable attention from the global community since the formation of the International Integrated Reporting Council (IIRC) in 2010. Mauritius is a fast developing country where IR has gained growing traction over the last three years. It is important to understand the potential for IR in this island where sustainable development must be central to economic thinking as the island state has to preserve its resources in the long run. The purpose of this paper to find out the organizational benefits and implementation challenges of preparing an Integrated Report in Mauritius. It is also extended to identify the knowledge and skills employers perceive relevant for future accounting graduates. A survey is carried out to extract responses from report preparers and other stakeholders (investors, analyst and auditors) from a wide range of industries in Mauritius, to explore their opinions regarding IR. Findings signify that IR is being adopted by a majority of companies in Mauritius, although it is a relatively new concept. A majority thinks IR is improving the current corporate reporting. However, the fear of divulging market and/ or price sensitive information is the main challenge facing the practices of IR in Mauritius. The findings may be useful to better understand the likely development of IR in developing markets, as most of the previous studies on IR focused on developed countries and South Africa.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".