Disasters, Nursing, and Community Responses: A Historical Perspective
Bibliographic record
Abstract
Modern disaster planning has taken on increased importance and urgency in light of recent dramatic increase in natural and man-made that resulted in enormous human and economic losses.1 Such planning is aided by examining historical role of nurses in disaster responses. Nurses occupy vital positions in disaster care because of their unique roles with pa- tients and their experience in such areas as evacuation, triage, physical and psychological care, screening measures, case finding, vaccinations, monitor- ing, and disease surveillance and prevention.What does history tell us about nurses' roles in disasters, particularly their provision of disaster relief during initial response phase? Why is this important for disaster responses? And how can this knowledge enhance our understandings of notion of phenomena? For this discus- sion, disaster is defined as a social disruption resulting from natural causes such as earthquakes and hurricanes, technological causes such as explosions or nuclear accidents, and conflict situations such as wartime.2 Research on term behavior has been a significant feature of disaster stud- ies in sociology, but it has not been examined from standpoint of history of nursing. Sociologists Thomas Drabek and David McEntire argue that emergent phenomena include the appearance of interorganizational networks after disaster which attempt to fulfill important societal functions made evident by an extreme event. These networks are composed of many organizations that work together to resolve demands placed on their community in times of disaster.3 Drabek and McEntire argue that people become more cohesive and unified during situations of collective stress, and they work together. Emergent groups often have no previous knowledge of each other, and they may perform nonregular tasks. Local communities are particularly important at this time; they are first to help themselves.4 Often, these emergent groups are most effective and quickest to respond after a disaster.5A history of nursing can contribute to theoretical discussions of emergent behavior. By taking into account nurses' rich heritage in disaster responses, we can learn about which groups should be included in any organizational coordination during disasters.6 This article features case studies of work of nurses and some physicians situated within a local response and one involving international aid. The aim is to enhance understanding of social and po- litical forces that informed nurses' actions and tensions and inconsistences that occurred at particular times in particular places.Doing disaster research has its challenges because records can be lost or destroyed. Some sources are available, however, including newspapers, diaries, letters to family members and other personal correspondence, offi- cial histories from organizations, city records, photographs, and oral sources. Problems include memory loss if a letter was written or an oral history obtained some years later. Yet Joseph Scanlon, who wrote about 1917 Halifax, Nova Scotia, ship explosion, found that disasters are so dramatic that many vividly remember what happened even three-quarters of a century earlier.7Another problem is history is recorded? From whose perspective? A gaping hole includes voices of silenced, including minorities, poor, and others excluded from power. This could be because they may lacked means to document personal experiences, or archivists and librar- ians simply did not seek their stories.8 In my own research, I had to doggedly piece together different sources and read between lines of others to get at silenced voice.In 2010, Arlene Keeling and I edited a book on history of nurs- ing in disasters.9 We concluded, based on 13 case studies, that nurses made crucial independent decisions in crisis situations where time was critical to a person's survival. …
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.006 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".