Proceed with Caution: Research Production and Uptake in Conflict-Affected Countries
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
The effectiveness of (neo)liberal intervention in conflict zones remains ambiguous, with supportive and critical camps of scholars and practitioners embracing disparate viewpoints that are each propped up by rigorous empirical analysis. The consequences of this empirical ambiguity have deeply permeated international intervention organisations, who use these unsettled findings for decision- and policy-making. This article argues that the promotion of disparate intervention methodologies is entirely predictable given the existence of contested relationships between prominent underlying themes to the debates around peacebuilding and development intervention: globalisation, development aid, inequality, and poverty, and their roles in inciting or preventing violence. These contested relationships justify the cautious selection and interpretation of research findings by decision- and policy-makers. The concluding discussions explore the impact of biased research production and uptake processes that bolster self-interested intervention practices and outline several recommendations for better aligning evidence-based decision- and policy-making with the needs of conflict-affected populations.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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