Bankruptcy reform in the Middle East and North Africa: Analyzing the new bankruptcy Laws in the UAE, Saudi Arabia, Morocco, Egypt, and Bahrain
Bibliographic record
Abstract
Abstract For years, countries in the Middle East and North Africa (MENA) region have been trying to increase entrepreneurship rates and attract foreign investment, however, their bankruptcy statutes remained antiquated and punitive in nature. Potential start‐ups and foreign investors have been deterred from these markets due to a lack of alternative solutions to liquidation and a fear of punishment for business failure. At least seven countries in the region have now taken steps to modernize their bankruptcy laws to provide restructuring mechanisms and other measures designed to incentivize risk‐taking rather than to deter it. With this year's crash in oil prices, an unprecedented global pandemic and an imminent recession, an effective bankruptcy system has become even more critical to avoid catastrophic results for the employment rates and economic value of the companies in the region. However, despite these recent reforms, significant improvements are still needed to maximize the value and benefits of bankruptcy procedures in the face of these growing economic threats.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".