Evaluation in Conflict Zones: Methodological and Ethical Challenges
Bibliographic record
Abstract
This article explores the methodological and ethical challenges particular to the conduct and use of evaluations in conflict zones. It does this through examining the synergistic interaction of conflict dynamics and the four domains of evaluation — ethics, methodology, logistics, and politics. Drawing on evaluation theory and practice, as well as field experience, the article seeks to contribute to the building of a more methodologically self-conscious sub-field of evaluation in conflict zones — with implications not only for the field of evaluation, but also for researchers and practitioners in the fields of development, humanitarianism, peacebuilding, and private sector investment.
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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 | 0.688 | 0.678 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.009 | 0.062 |
| Scholarly communication | 0.027 | 0.022 |
| Open science | 0.007 | 0.018 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".