E<scp>mpowerment or </scp>I<scp>mposition? </scp>D<scp>ilemmas of </scp>L<scp>ocal </scp>O<scp>wnership in </scp>P<scp>ost‐</scp>C<scp>onflict </scp>P<scp>eacebuilding </scp>P<scp>rocesses</scp>
Bibliographic record
Abstract
This article examines questions of local ownership in post‐conflict peacebuilding and makes the case that the complex relationship between insiders and outsiders lies at the very heart of contemporary peacebuilding processes. While the discourse of local ownership has increasingly become part of the vocabulary of post‐conflict peacebuilding, the discussion to date on both the meanings and the practices of local ownership in peacebuilding contexts remains underdeveloped. This article is therefore an effort to add substance to the local ownership debate, and outlines two forms of peacebuilding—liberal and communitarian—which contain markedly different assumptions concerning the role of local actors in peacebuilding processes. Ultimately, the article suggests that the search for ways to operationalize local ownership principles remains one of the key challenges of contemporary peacebuilding, and outlines a vision of peacebuilding as cultural exchange as a way forward.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| 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 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.086 | 0.012 |
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".