Standardising and mapping open‐source information for crisis regions: the case of post‐conflict Iraq
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Painting an accurate picture of the situation on the ground in countries in crisis is vital for the efficiency of humanitarian aid and reconstruction agencies. This study describes a method for standardising and mapping the plethora of open-source information. The test site for the study is post-conflict Iraq. Important information on aid distribution, reconstruction and security in Iraq can be derived from the reports of humanitarian aid agencies and the media, before being formatted, inserted into a database and mapped. The product is a visual, cartographic structure of otherwise random information, showing which organisations are working in the country, which thematic and geographic areas are being prioritized in the field, and which areas most frequently experience security events. This type of mapping not only highlights the overall working environment within different parts of the country, but it may also serve as a decision-making tool for donors and humanitarian aid agencies planning to deploy personnel.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it