An Empirical Study Evaluating the Adoption of Mobile Bankingin Sudan
Bibliographic record
Abstract
This study is about the revolution of information and communication technology (ICT). It deals with the evolution of banking technology (BT), electronic banking (e-banking) and mobile banking (m-banking) in Sudan. It intends to explore the practice of m-banking in Sudan. The focus is on the availability of adequate infrastructure and on the challenges and risks that face m-banking services in Sudan. The findings showed that although mbanking is believed to be essential, still the services provided are at an infant stage. It is also found that concerned parties are not fully cooperating. This raises risks and constitutes challenges that hinder full utilization of m-banking in Sudan. Based on these results, the main recommendation of the researchers was that regulatory policies should be stated clearly to ensure full collaboration between all concerned parties. This is to support bank managers and decision makers in formulating their strategic plans to deliver competitive services.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".