Towards Evacuation Equity: An Analysis of Needs, Challenges, and Choice-Making Patterns
Bibliographic record
Abstract
Climate change, extreme weather events, and human-initiated disasters pose increasing threats to cities globally. The impacts of disasters, however, are not experienced equally. Previous literature and events have consistently shown that underserved groups – such as older adults, individuals with disabilities, lower-income households, and carless residents – bear disproportionate impacts of emergencies, and often account for a significant share of injuries and fatalities. Despite this trend, evacuation planning in North America has generally followed traditional metrics of transportation efficiency, sometimes leaving behind vulnerable populations who primarily rely on public transit for mobility. Consequently, research and practical tools are needed to develop evacuation strategies that are multi-modal and inclusive of underserved groups. This thesis contributes to the literature by 1) assessing current evacuation practices as they relate to underserved groups, 2) providing an understanding of underserved groups’ transportation needs and challenges during emergency evacuations, and 3) empirically examining the factors affecting evacuation choice-making among underserved groups. In this research, a mixed methods approach grounded in human-centred engineering was employed to comprehensively work towards an understanding of underserved groups’ transportation needs and decision-making processes during evacuations. A systematic literature review was first conducted to examine previous research and synthesize findings related to the role of public transit in emergency evacuations. A focus group methodology was then undertaken – with Edmonton as a case study – to ascertain emergency preparedness and transportation needs among underserved groups. Finally, an empirical study was performed, using stated-preference survey data and discrete choice modelling, to understand evacuation choice-making patterns among underserved groups in Alberta and British Columbia. This thesis uncovered five key insights: 1) despite notable heterogeneity among underserved groups, most evacuation research does not differentiate between distinct groups’ transportation needs, 2) many jurisdictions in North America, including Canada, still lack public-facing evacuation plans with transit considerations for those with limited mobility 3) reliability, accessibility, and affordability of public transit are vital for ensuring its effectiveness during emergencies, 4) public transit can potentially serve as a tool for building community cohesion and mitigating anxiety during disasters, and 5) socio-demographic characteristics and previous evacuation experiences have significant influences on key evacuation decisions including mode and shelter choices. Based on these findings, policy recommendations provided for local agencies include ensuring public-facing, multi-modal evacuation plans with transit considerations for underserved groups, strengthening inter-agency collaborations, and providing targeted engagements and emergency preparedness programs for underserved groups. In highlighting the need for tailored evacuation strategies, this thesis provides the necessary groundwork for emergency management officials, transportation engineers, and policymakers to more effectively address challenges faced by underserved groups in future emergency events.
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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 | 0.013 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".