Bibliographic record
Abstract
Recent decades have witnessed a shift in development practice whereby donors increasingly provide aid to support security-related programming in the Global South. Over this same period, there has also been an increase in violence committed against aid workers. This paper explores whether these two phenomena are correlated by analysing aggregate data on securitized foreign aid flows and data on violence against aid workers from the Aid Worker Security Database (AWSD) for the period 1997 to 2019 using cross-national multivariate analysis. Our findings reveal that, regardless of all other contextual and opportunistic control variables, there is a direct correlation between the increased inflow of securitized forms of aid to recipient countries and a sharp rise in violence against humanitarian workers in those countries. We hypothesise that this is because this form of aid alters the environment for aid work in three key ways: (1) it introduces aid to a changing and more complex political context; (2) it prompts increasingly risky aid worker behaviour; and (3) it provides opportunity to those groups and individuals who might attempt to benefit from violent acts against aid workers and organisations. As securitized aid continues to increase, attacks on aid workers will likely also rise, which should be a policy concern for humanitarian agencies.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".