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
Sharing evidence on humanitarian reliefNeeds a publicly accessible, searchable, and comprehensive database O ne year ago the Asian tsunami struck, resulting in the largest humanitarian efforts of our generation.This year's hurricane Katrina and earthquake in Kashmir also showed that both developed and developing nations are ill prepared for major disasters.Rapidly sharing relevant information from relief agencies and academic and non-government organisations (NGOs) at such critical times can make an important difference to tens of thousands of people.Relief agencies conduct fact finding expeditions in emergencies, as well as important public health measurements such as water testing, measles surveillance, and conflict surveillance.Their reports often provide the most up to date and relevant evidence on relief situations, 1 but are too often shared only internally.For agencies and field coordinators to make informed decisions, access to this information is vital.We must, therefore, consider how to create and disseminate evidence regarding humanitarian interventions. 2 One absolute necessity is a publicly accessible, searchable, and comprehensive database on humanitarian disasters and approaches to relief.The lack of systematically documented or disseminated information leads to unnecessary duplication of efforts and ill informed decisions.Given the inadequacy of funding for relief aid, resources must be used wisely.Some relief databases are already accessible to the public and NGOs.The largest is Relief Web (www.reliefweb.int),established in 1996 by the United Nations, but it has been hindered by a lack of submissions from agencies and a reticence by academics to submit reports that may be under review at journals.Other resources include the SHARED Global Database, ELDIS (the Electronic Development and Environment information System), and ID21 (Information for Development in the 21st Century), but these have the same drawbacks as Relief Web and their reporting styles vary widely.Large NGOs and international agencies have, at times, maintained publicly accessible databases; smaller agencies sometimes post reports on their websites.None of these resources is sufficiently comprehensive.A comprehensive database would have many aims but would also have to overcome certain challenges (box).Furthermore, the quality of evidence needs to be considered.The thresholds for acceptable evidence on humanitarian situations may be different from those for therapeutic interventions, 3 and a formal hierarchy for it has not yet been established. 1 4Access to reports may allow evaluation of the effects of interventions
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.011 |
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