Proceed with Caution: Research Production and Uptake in Conflict-Affected Countries
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.
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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 | 0.621 | 0.824 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.009 | 0.033 |
| Scholarly communication | 0.022 | 0.020 |
| Open science | 0.011 | 0.018 |
| Research integrity | 0.017 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".