Empowering communities for peace: Multitrack strategies for sustainable peacebuilding in Africa
Bibliographic record
Abstract
The paper discusses approaches and analyzes strategies that has the potential to effectively address the root causes of conflicts and promote long-lasting peace in Africa. The study utilizes the concept of multitrack diplomacy theory to explore various interventions and strategies that might contribute to the transformation and prevention of conflicts. It emphasizes the importance of comprehensive approaches that involve citizen diplomats, political elites, religious leaders, NGOs, the media, conflict resolution educators, and traditional rulers. The paper underscores the need to involve and empower local communities to give them a sense of ownership and authority over peacebuilding initiatives. Storytelling, interfaith activities, legal accountability, and education are recognized as useful methods for promoting reconciliation, preventing trauma, and developing the ability to resolve conflicts. The literature indicates that adopting a relationship-focused strategy, bolstered by multitrack diplomacy and local empowerment, can play a role in achieving lasting peace in Africa and other regions. The paper offers pragmatic insights for policymakers, practitioners, and stakeholders engaged in peacebuilding endeavors. It emphasizes the significance of promoting conversation, harmony, and shared comprehension while taking into account the specific requirements, objectives, and resolutions of the local community. By employing these tactics, individuals or groups with a vested interest in a particular issue can actively strive to bring an end to harmful disputes and facilitate inclusive processes of change that foster positive and enduring peace.
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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 | 0.007 | 0.006 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| 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".