Flooding and the ‘new normal’: what is the role of gender in experiences of post‐disaster ontological security?
Bibliographic record
Abstract
Disaster researchers have long analysed disruption to affected residents' ontological security, often represented by routines and familiar landmarks. Surprisingly little of this work, though, assesses who is most likely to experience feelings of disruption. Using a representative set of survey data, complemented by follow-up interview data from 40 residents affected by the Southern Alberta Flood of June 2013, this paper explores how demographic characteristics, such as gender and place attachment, impact on residents' sense of disruption and loss. The findings indicate that women and people with stronger emotional and social ties to their neighbourhoods are most likely to experience disrupted ontological security; home flooding and evacuation orders are also significant predictors. The qualitative interview data reveal that many participants felt unsettled and disrupted by myriad factors, such as ongoing construction, which prevented them from establishing a 'new normal'. The paper concludes by discussing the implications of these findings for policymakers and service providers.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".