Containing Ebola: A Test for Post-Conflict Security Sector Reform in Sierra Leone
Bibliographic record
Abstract
Ebola has provided the greatest test of the Sierra Leonean security sector – and, in turn, of the UK-led reforms of the past ten-to-fifteen years. The performance of the country's security forces at the height of the crisis suggests that there are sound structures in place; however, Ebola has shown that the Government of Sierra Leone's national security architecture still lacks maturity in responding to such a scenario.Drawing on first-hand interviews with advisers on the ground, this article explores the Sierra Leone government’s response to the Ebola crisis and the performance of the security sector so far, within the wider context of UK-led security-sector reform (SSR) since the end of the civil war. In doing so, it highlights a number of lessons to have emerged from the crisis, exploring what these reveal about the nature of the reforms implemented since the end of the country's civil war. In turn, it explores what these suggest for future SSR, which continues to be a core component of the UK’s approach to development and overseas capacity-building.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".