Memoirs of women-in-conflict: Ugandan ex-combatants and the production of knowledge on security and peacebuilding
Bibliographic record
Abstract
Abstract The limitations of conventional accounts of security and peacebuilding drawing upon the ‘expert’ knowledge of military elites, policymakers and civil society representatives have been widely recognized. This has led security and peacebuilding policymakers, including through the United Nations Women, Peace and Security agenda, to search for alternative forms of knowledge, such as memoirs, photographs or oral histories, that better reflect lived experiences within local communities. Building on existing work on memoirs as knowledge production artefacts and on feminist security studies, this article demystifies experiential security knowledge through an analysis of three memoirs written by women ex-combatants in Uganda. We argue that while the memoirs offer complex and contradictory narratives about women ex-combatants, they are also the products of transnational mediated processes, whereby the interests of power translate complex narratives into consolidated representations and sturdy tropes of the abducted African woman ex-combatant. This means that although the three memoirs provide some hints as to transformative ways of thinking about security and peace, and offer dynamic accounts of personal experiences, they also reflect the politics of dominant representational practices.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.021 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".