Strategic Frameworks that Embrace Mutual Accountability for Peacebuilding: Emerging Lessons in PBC and non-PBC Countries
Bibliographic record
Abstract
This article examines the use of strategic frameworks in four countries emerging from conflict with a view to understanding the extent to which they have served to contribute to more effective peacebuilding outcomes. Two of the cases examined (Sierra Leone and Burundi) are currently on the United Nations Peacebuilding Commission's agenda, and two (Liberia and Afghanistan) are not, although they both host a United Nations peace mission. Core elements suggested as necessary for strategic frameworks to contribute to better peacebuilding include giving attention to: 1) addressing sources of conflict; 2) strengthening national capacities; 3) promoting coherence, coordination and integration among various actors; and 3) establishing mutual accountability of national and international actors. Comparative findings illustrate the need for more sustained attention to these issues within strategic frameworks in the collective search for sustained peace in conflict-affected countries.
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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 | 0.025 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.009 | 0.033 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| 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".