THE GROWING ISSUE OF BUSINESS FRAUD IN BURKINA FASO: WHAT BEST PREVENTION DEVICE?
Bibliographic record
Abstract
This study shows the state of fraud in businesses in Burkina Faso while diagnosing anti-fraud schemes. Thanks to this research carried out on Burkinabè companies, the results show that fraud affects all sectors of activity. It also exposes the limits of anti-fraud systems, which are essentially: the limits of the organizational framework, the weakness of the internal control system and the lack of an anti-fraud culture. To conduct our research, a quantitative approach is used to collect and interpret the data and the qualitative approach to deepen the analyzes. The results show that fraud is very real and affects the majority of companies: among the causes are weaknesses in internal control systems. To do this, we have proposed ways to identify the risks of fraud, thwart them and prevent them. This concerns particularly the mapping of fraud risks and the implementation of the anti-fraud system.Keywords: Fraud, Business, Prevention, Systems.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".