Praetorianism the Public Service: Analysis of the Impact and Consequences of Military Rule on Public Administration in Nigeria
Bibliographic record
Abstract
The purpose of this paper is to examine the impact and consequences of military rule on the Public Service in Nigeria, as well as the major challenges that confront this principal administrative machinery of government in its drive to adjust itself to the demands of true democracy and good governance in Nigeria. This is done with a view to highlighting areas of emphasis in the on-going efforts at reform of the Public Service, and to make relevant recommendations towards making it more focused and adaptable to the needs of a truly democratic dispensation. Making use of library research methodology, the paper examined the impact and consequences of Military praetorianism upon the Public Service in Nigeria, especially as it relates to contemporary issues and challenges faced by the Nigerian Public Service. Listing viable alternative futures, the paper proffered new possibilities and solutions for re-positioning the Public Service, and urged Public Servants to rise up to the challenge of new innovations, and a new approach made mandatory by the imperatives of a new democratic order in the Country. The paper concluded that in this age of reforms the Public Service must accept the challenge of re-inventing itself and return to its pride of place. To do this the civil servant must shed the toga of civil master and rededicate itself to an irreversible return to the “tap” instead of aiming for the “top”.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".