Toolkit for transformative mediation in peacebuilding
Bibliographic record
Abstract
This toolkit responds to increased interest in the “contribution that mediation can make at all levels of a conflicted society.”1 It does so by introducing innovative strategies for transformative mediation and inclusive dialogue in peacebuilding contexts. The toolkit expands the range of actors, knowledges and practices that can be mobilised to achieve greater inclusion in mediation and peacebuilding, and emphasises the importance of transformative approaches built around openness and diversity. While peace mediation is traditionally understood as a set of practices and interventions leading to a peace agreement, this toolkit employs a more expansive understanding of mediation as intrinsically connected to wider processes of conflict transformation. Consistent with a conflict transformation approach that views building peace as an ongoing process, the toolkit outlines recommendations on how transformative mediation practices can be sustained long after the signing of a peace agreement. Findings and recommendations are drawn from research carried out in Northern Ireland with a diversity of mediators, peacebuilders, and activists.
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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 | 0.014 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.181 | 0.061 |
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".