The Perils of Power-Sharing: Africa and Beyond
Bibliographic record
Abstract
The purpose of international conflict-resolution efforts is, in the short term, to bring an end to violent armed conflict, and, in the medium to longer term, to prevent the revival of conflict. However, at least one of the mechanisms often utilised in conflict resolution and peace agreements, power-sharing, may not only prove problematic in early negotiation and implementation, but may potentially be at odds with the longer-term goal of preventing resurgence of conflict. Why might this be the case? Longer-term peacebuilding seeks to prevent conflict in part by building strong and sustainable states. Such states should be able to avoid reverting to armed conflict because they would be more responsive to grievances and more effective in dealing with violent dissent. However, power-sharing arrangements may undermine such efforts by placing in power individuals and groups not fully committed to, or unable to take part in, governance for the benefit of the entire populace; in part because it necessarily places in power those who have engaged in significant violence to achieve their ends. This is likely to create less democratic states, although we do not insist that democracy is or should be the only goal of peacebuilders. Rather, we suggest that power-sharing arrangements may tend not only towards undemocratic states, but towards states which are not responsive to the needs of the citizenry for security in ways which may undermine human security and state legitimacy.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.007 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".