Strong Institutions and the Challenge of Democratic Consolidation in Nigeria’s Fourth Republic
Bibliographic record
Abstract
This article examines the challenge of democratic consolidation in Nigeria’s Fourth Republic and the role that strong institutions could play in overcoming it. It posits that against the backdrop of endemic and systemic corruption, economic crisis, manipulation of both the electoral and constitutional arrangements for personal and party advantages, political exclusion, attempts at blackmailing and/or emasculating both the legislature and judiciary by the executive, intolerance of opposition by ruling political parties and a tendency towards authoritarianism, it is obvious that democracy is under threat in the nation’s Fourth Republic. These challenges have the capacity to derail the country’s current democratic experiment and/or cause democratic breakdown. The paper argues that institutional weakness is the bane of democratic consolidation in the Fourth Republic. It concludes by recommending the strengthening of political institutions as a panacea to the challenge of democratic consolidation in the country and align with the argument that strong institutions, far more than “strong men”, are needed to overcome the challenge of democratic consolidation in a country at a developmental crossroads.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 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".