The Impact of Food Assistance on Pastoralist Livelihoods in Humanitarian Crises: An evidence synthesis protocol
Bibliographic record
Abstract
This protocol outlines plans for conducting an evidence synthesis on the impact of food aid on pastoralist livelihoods. The distinctiveness of pastoralists - including factors related to the erosion of their livelihood strategies and the difficulty posed by identification of frequently mobile households - and their particular vulnerability to humanitarian crises suggest that the effects of humanitarian interventions targeting them are likely to differ from other populations. The purpose of this review is to use evidence synthesis methods to: systematically identify all available evidence on the impact of food assistance to pastoralist livelihoods (during and after) a humanitarian crisis; compare and contrast the effects of assistance delivered (by population, assistance type etc.); qualitatively and (if possible) quantitatively synthesize identified data and concepts; assess the quality of evidence, as appropriate; and identify gaps in the current evidence-base and further comment on future research needs in this space. To the review team's knowledge, this will be the first evidence synthesis that specifically addresses the impacts of food assistance provided in the context of humanitarian interventions on pastoralists' livelihoods. This review is commissioned under the Humanitarian Evidence Programme, a UK Aid-funded partnership between Oxfam and Feinstein International Center that aims to improve humanitarian policy and practice.
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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 | 0.167 | 0.194 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.011 | 0.017 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.098 | 0.014 |
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".