The ICRC's approach to urban services during protracted armed conflict: Q & A with Evaristo de Pinho Oliveira
Bibliographic record
Abstract
Evaristo de Pinho Oliveira is the head of the International Committee of the Red Cross (ICRC) Water and Habitat Unit. He started working with the ICRC as a water and sanitation engineer in 1995. Over the next ten years he completed missions in Bosnia-Herzegovina, Angola, Iraq, Sudan and East Timor, and provided water and habitat support to the ICRC's regional delegations in Asia. He then was based at ICRC headquarters in Geneva, where he held several positions supporting field operations in Asia, the Middle East and Eastern Europe. In 2016, he co-authored the ICRC's report on Urban services in protracted armed conflict: A call for a better approach to assisting affected people . Prior to working at the ICRC, he worked in Quebec as an engineer and as a teaching assistant at McGill University.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".