Security Challenges of States Building Crisis in West Africa since 1955
Bibliographic record
Abstract
West African states have been struggling to build their nation-states since the independences that started in 1957. The same ills that struck these states since the beginning seem to have stuck with them despite several attempts at healing them. Instead of modern and prosperous states, people are witnessing the chronic weakness of their states. This research seeks to contribute to the understanding of states’ weakness in West Africa and to the analysis of possible solutions to address the problem. The opening chapter sets the stage of the research by introducing the phenomenon of states’ weakness in West Africa. The next chapter looks at the literature that deals with states power and weakness. The frames of analysis used to evaluate these states’ strength and weaknesses are also introduced in this chapter. These are the critical mass, political skills, economic wealth, military and security assets. These resources offer a view of a state’s potential. Chapter three delves on some of the causes of West African states’ weakness. These states are weak because of the structures and internal socio-political dynamics within them. Some other causes of their weakness come from the global powers’ influences. The last section of the chapter offers an overview of how the Cold War (1945-1989) influenced events in the sub region. The political environment of overlay by global powers shapes considerably the states under study. Security Reform and Governance is posited as the solution to the lack of capacity of West African states. Chapter four of this work delves on this subject. The security sector covers most state’s institutions that need to be reformed in West Africa. The closing chapter demonstrates how the Economic Community of West African States is a nascent security community. Its security architecture endorses the Security Sector Governance mechanism and therefore stands a better chance of strengthening member states if provided with the needed resources.
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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 | 0.001 | 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".