Bibliographic record
Abstract
Purpose – Natural disasters, occurring with increasing frequency are mobilizing humanitarian agencies to provide relief response. Current protocols that rely heavily on donated clothing as clothing aid are neither effective nor efficient. The purpose of this paper is to investigate survivors’ clothing needs during the relief phase of a natural disaster in order that current protocol might be improved. The focus is on clothing use from the perspectives of survivors who will wear it, relief workers and aid agencies that will disperse it. Design/methodology/approach – This qualitative study included needs analysis focus groups with survivors, interviews with relief aid workers and senior humanitarian agency administrators. All respondents were residents of and/or impacted by the 2005 earthquake in Pakistan. Questions focused on relief aid protocol, clothing needs and mandatory requirements for a design solution. Findings – Data gathered revealed a myriad of design priorities and participants emphasized that garments be culturally and climatically appropriate and universal in design. Based on these criteria, a prototype (named Survival Plus) was created using the Functional, Expressive and Aesthetic design framework as proposed by Lamb and Kallal (1992). Research limitations/implications – Further research may be undertaken to field test proposed Survival Plus prototype to evaluate the design and subsequent findings be incorporated in its design. Originality/value – Academic knowledge about this aspect of disaster management and response is scarce. This participatory study of clothing needs of survivors is of particular benefit to emergency preparedness initiatives and humanitarian aid providers in their delivery of clothing aid.
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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".