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 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 | 0.016 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".