Including Perspectives of Women Using ICTs to Promote Peace in the Anglophone Crisis in Cameroon
Bibliographic record
Abstract
Information and Communication Technologies (ICTs) offer valuable tools for fostering social cohesion and conflict resolution, yet little is known about women's roles in this domain. This study draws on 14 interviews to explore how female Cameroonian peacebuilders used ICTs during the Anglophone Crisis. Findings indicate that low-tech tools, like WhatsApp groups, play a key role in information dissemination, while more advanced technologies remain largely absent despite their growing presence in peacebuilding literature. Whilst this study demonstrates the capacity of ICTs to promote women's involvement in peacebuilding by facilitating participation, protection, and prevention, it also examines existing challenges, including restricted accessibility and technology-facilitated violence. By exploring the intersection of digital peacebuilding and the UN's Women, Peace, and Security Agenda through the lens of the Cameroonian case, we propose an intersectional feminist digital peacebuilding framework, incorporating gender-responsive and locally grounded strategies to better support women's engagement in peacebuilding efforts.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".