Resources Management and Economics Development in South Sudan, Case Study of Ivory Bank, South Sudan, Juba
Bibliographic record
Abstract
This study is focusing on how bank financial resources can be increased by Ivory Bank in provision of financial services through of its branches. The research was conducted to demonstrate Resource Management in the bank. It involved explanation of historical development of banking and development system since the establishment of the Bank up to today. Also, it considered the development of Resource Management according to early thinker about management during Industrial Revolution. This is revealed by the study that the goal of resource management is to use the best combination of banking activities to satisfy bank customers. Therefore study considered the research analysis shown sectors benefiting more indicate, all customers mentioned above has the higher percentage. While in attention of bank authority for staff training, short courses Inside the Country follow, and reasons for choosing Ivory Bank, Bank nearer to Customers residence or market obtained more reasonable half percentage study analysis. Moreover reasons why customers got attracted to deal with bank, the question was about quick and reliable, accuracy, confidence, flexibility, the only bank in the area and all above the result has shown all mentioned above has the higher percentage of more than three quarter of sample size. All this indicate the result of study has demonstrate that, bank maintain more clients and is able to make resource management efficient and in turn increases chances for bank economic growth. This can increase the improvement of population standard of living although high running inflations affect these efforts. However there some challenges facing bank as shown study analysis, which could solve through staff motivation by bank management.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".