"Engendering" Change in Disaster Response: Increasing Women in Leadership Roles
Bibliographic record
Abstract
Disaster response has has historically emerged from male dominated military institutions. Skills emphasized as advantageous by respondents in police, fire, and paramedic fields were physical strength and prowess, typically attributed to the male gender. As a result of these fields being almost exclusively male dominated, management obtained through internal promotion was usually male as well, especially since idealized leadership traits are often misattributed to males. Some studies have found that leadership in complex stressful operations requires an appraisal of what is at stake and the manageability of a situation, but these findings lack information on the competency of women in such roles. The absence of women in senior disaster management positions may indicate that the entire process of selection, recruitment, and promotion in a system needs to be revamped. The nature of response in the face of disaster in the modern era increasingly employs completely different skill sets and an ever broadening inclusion of various disciplines. Despite these changes, leadership in disaster response continues to perpetuate the stereotypes of what management in the field should be, and continues to be predominantly male. This paper will briefly summarize some of the advantages to increasing the number of females in disaster management and some strategies to practically transform an organization in order to promote such inclusion.
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How this classification was reachedexpand
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 | 0.012 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".