The Military And The Challenge Of Democratic Consolidation In Nigeria: Positive Skepticism And Negative Optimism
Bibliographic record
Abstract
Nigeria like several other countries in Africa, Asia and Latin America depicted the picture of a ‘praetorian state’ or what Leo Dare called the ‘praetorian trap’. The reason for this nomenclature is not far fetched. The polity alternated between civilian and military administrations since her ‘flag independence’ in October 1960. The only respite so far is the uninterrupted civilian administration since May 29 1999, when the nascent democracy was inaugurated. Even at that, the risk of military intervention has not completely evaporated from the political firmament. The thrust of this paper, however, is an in-depth analysis of the role(s) of the military in democratic political transitions in post-colonial Nigeria. This study becomes imperative in the context of the military superimposed democratic transitions in Nigeria. In a nutshell the paper recognizes the fact that much as the military as an institution had been promoting democracy, they have also been truncating same – a kind of contradictory compatibility – thus making Nigeria laboratory for testing military role(s) in democratic transitions.
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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 | 0.007 | 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 | 0.010 | 0.018 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".