The humanitarian theatre: drought response during Ethiopia's low-intensity conflict of 2016
Bibliographic record
Abstract
Abstract This article aims to rekindle the debate on the politics of aid in the increasingly common – yet still under-studied – authoritarian and low-intensity conflict settings, detailing the case of Ethiopia in 2016, when a 50-year drought coincided with a wave of protests and a state of emergency. During four months of qualitative fieldwork in 2017, state, civil society, Ethiopian and international actors were approached – from humanitarian headquarters to communities in the Amhara, Oromiya and Somali regions. Research participants relayed stark discrepancies between the humanitarian theatre's ‘frontstage’, where disaster responders showcase an exemplary response, and its ‘backstage’, where they remove their frontstage masks and reflect on the information, the decision-making monopoly of the state and the intrusion of conflict dynamics into the humanitarian response. In humanitarian research and in policy, a collective conversation is necessary on where to draw the line between respect for governments’ sovereignty and the intrusion of humanitarian principles.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".