DEVELOPING A SHELTER EVALUATION INSTRUMENT THAT PROMOTES POST-DISASTER POPULATION HEALTH
Bibliographic record
Abstract
Introduction Absence of shelter may adversely affect the health of post-disaster populations. When shelters are inadequate or not provided, overcrowded ad hoc communities may form and encourage the spread of infectious disease. Shelter evaluation is therefore necessary to promote post-disaster population health. Even in cases where evaluations are carried out, standardized evaluation indicators do not exist. Objectives To determine what indicators are being used and which should be used to evaluate shelter assistance following natural disasters. Methodology 1. Review: Using systematic review methods, electronic databases and the grey literature were searched for publications that evaluated shelter assistance following natural disasters in developing countries. Indicators used to evaluate shelter assistance were extracted and the most common indicators were identified. 2. Interviews: Based on the indicators extracted, a preliminary evaluation instrument was designed to evaluate shelter assistance. Six shelter experts were interviewed to establish validity of the indicators and evaluation questions. The transcripts from the interviews were analyzed using rigorous qualitative research methodology. Results 1. Review: A total of 1480 indicators were extracted from 181 publications. Indicators most commonly evaluated in the field were: community involvement in shelter planning (n=108), quality and labour of construction (n=107), and scale of assistance provided (n=99). 2. Interviews: Shelter experts felt that the correct indicators had been extracted; however, they expressed the need for more health related indicators. They also felt that the questions evaluating the indicators measured output and should be rephrased to evaluate outcome and impact. Conclusions This evaluation instrument, directly based on the most important indicators in the literature and validated by shelter experts, will enable aid agencies to better assess and meet the shelter and health needs of populations impacted by disasters.
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.
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 | 0.209 | 0.236 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.020 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".