Federalism and Contending Issues in Contemporary Nigeria: Mapping Alternative Perspectives for a Neo-Federalist Paradigm
Bibliographic record
Abstract
Evidence abound that Nigeria’s form of federal system has been grappling with serious working and institutional challenges. The paper interrogated contending issues ravaging Nigeria’s federal polity with a clarion call for timely adoption of neo-federalism paradigm. It employed qualitative research method with classical model of federalism as framework of analysis. The paper established that Nigeria’s federal republic is associated with over-concentration of governmental powers at the centre, sectional domination of powers and political leadership, inept and corrupt leadership/bad governance, socio-economic crisis, insecurity, corruption, favouritism and nepotism, problem of power sharing and poor implementation of federal character principle, which further heightened the delivery of socio-economic services and democratic dividends to the people. It concluded that for Nigeria’s federation to stand the test of time and overcome myriad problems it is currently facing, embracing the neo-federalism paradigm is inevitable. Among recommendations proffered include devolution of powers, adequate provision of sustainable security, and election of dedicated, committed and visionary leadership at all levels of government with the ability to drive the economic blueprints of this nation towards greatness, provide essential needs for the citizenry and promote good governance.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".