‘Living between Two Lions’: Civilian Protection Strategies during Armed Violence in the Eastern Democratic Republic of the Congo
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article examines how civilians assess, negotiate with, and in some cases deceive armed actors in the eastern Democratic Republic of the Congo (DRC). It demonstrates that civilians not only navigate the precarious and unpredictable conditions within armed conflict, but also exploit these conditions to improve their security situations. The ‘self-protection’ strategies analysed aim to prevent, mitigate and confront violent threats that civilians encounter in their daily lives. This article argues that civilian self-protection strategies are especially prevalent in contexts marked as ‘no peace – no war’. Characterised by prolonged and low intensity violence, ‘no peace – no war’ contexts shape civilian self-protection strategies in three ways. First, civilians often develop a sophisticated understanding of the actors involved and the patterns of violence that unfold. Second, civilians often learn what particular strategies are most likely to be successful, typically through trial and error. Third, civilians have often become sceptical and cynical about international actors and activities. Understanding what actions civilians take to protect themselves, their families, and their communities is critical for the international community's role in peacemaking and peacebuilding.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it