A Review of Contemporary Governance Challenges in Oman: Can Blockchain Technology Be Part of Sustainable Solutions?
Bibliographic record
Abstract
Oman is considering adopting the latest e-governance technology, including Blockchain-based. While much research was conducted into the benefits and risks of Blockchain-based in information systems and finance fields, fewer researchers investigated the opportunities and risks associated with adopting Blockchain-based frameworks for governance and public administration, especially in highly bureaucratic, centralized rentier states, such as Oman. As the first phase of an exploratory sequential mixed-methods study, our purpose was to identify key governance problems in contemporary Oman and analyze each problem against evidence drawn from the relevant parts of the Blockchain-based and e-governance literature to evaluate the potential utility, risks and limitations associated with adopting block-chained e-governance solutions in the Sultanate. Our initial results indicate that there are advantages for states, such as Oman, from being an early mover into block-chained e-governance systems, including greater cost efficiency, drastically improved accuracy and reliability of information systems, transparency and accountability of public services, and an upgrade in the overall level of legitimacy and public trust in the institutions of governance. However, more research into the risks related to reconciling block-chained systems with the dynamics of labor, tax reforms and centralized authority in a rentier social contract is required.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 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".