Contemporary Issues and Prospects towards Effective Implementation of Revenue Allocation in Nigeria
Bibliographic record
Abstract
he study examined the contemporary issues and prospects towards effective implementation of revenue allocation in Nigeria. Three research questions guided the study. The study adopted a descriptive survey research design. The population of the study comprised 288 budget Officers under the Federal Ministry of Finance. The instrument for data collection was structured questionnaire developed by the researchers: Implementation of Revenue Allocation Questionnaire (IRAQ). The instrument was face validated by three experts, two from the Department of Public Administration, National Opening University of Nigeria, Abuja Study Centre and one from the Department of Public Administration and Local Government Studies, Faculty of Social Sciences, University of Nigeria, Nsukka. The internal consistency estimates for the structured questionnaire items were established using Cronbach Alpha techniques of estimating reliability which yielded an overall reliability co-efficient of 0.84 indicated that the instrument was reliable for the study. Data were collected by three research assistants using direct delivery and retrieval technique. Mean and Standard Deviation were used to answer the research questions. The findings of the study revealed the contemporary issue of revenue allocation and identified challenges which embedded as outlining prospects for it. The findings of the study also revealed in a bid strategies to resolve the controversial issues surrounding the contentious revenue allocation in Nigeria, a high level of fiscal decentralization is require replacing the unfair revenue sharing formula currently on operations. Based on the findings, among the recommendations were that revenue formulae for revenue sharing should be guided by national interest, which should take precedence over individual or primordial attention and reactions. Keywords: Contemporary issues, prospects, revenue, revenue allocation, revenue formula
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".