Foreign Aid, Decentralization, Local Governance and Service Delivery in Local Governments: A Case Study of Rumbek Central County South Sudan
Bibliographic record
Abstract
The study focused on foreign aid, decentralization, and local administration to examine the gap in service delivery in Rumbek County, South Sudan. The study's goals were to investigate the connections between foreign assistance and service provision, the connections between foreign assistance, local governance, and service provision, and the study factor structure between foreign assistance, decentralization, local governance, and service provision. The study population consisted of 75,000 respondents, and the research style was a case study and descriptive research design. It used both qualitative and quantitative methodologies to gather data from this population. The sample of 382 respondents was chosen using simple random sampling. Only 352 were considered for analysis. The descriptive analysis option of SPSS version 20.0 was used to analyze the data before it was presented using Spearman's correlation, multiple regression, and factor structure loadings to show the relationship and prediction for international aid, decentralization, local governance, and service delivery, respectively. The major findings of the study were that there is a significant positive correlation between; foreign aid and service delivery (r = 0.728, P-value < 0.01), decentralization and service delivery (r = 0.544, P-value < 0.01), local governance and service delivery (r = 0.776, P-value < 0.01) and foreign aid, decentralization and local governance influenced 62.9% the level of service delivery. The study suggests that the county implements control measures to guarantee that funds are used for the proper purposes in the counties because research revealed that services were not worth the district budget. Adequate research should be conducted at the community level to identify services needed by the people to draw sufficient budgets for the implementation of foreign aid, decentralization, and local government.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".