Rhythms of Resilience: Residents’ Perspectives on Public Space and Seismic Adaptation in Buca, İzmir
Bibliographic record
Abstract
This study examines how Hasan Aga Park in Buca, İzmir functioned simultaneously as an everyday public space and emergency infrastructure after the 30 October 2020 earthquake, interpreting residents' behaviors and perceptions through the lens of urban "rhythm."A qualitative design combined field observation with a retrospective cross-sectional survey of 40 residents who used the park during and after the event.Descriptive statistics and thematic analysis were integrated to map patterns of movement, gathering, perceived safety, facility adequacy, and emotional meaning.Residents rapidly converged on the park due to proximity, familiarity, and visibility, redefining it from a leisure landscape to "temporary home" and "safe zone."Accessibility and municipal/volunteer coordination underpinned feelings of safety and order, while inflexible furniture and inadequate sanitation constrained adaptability.Design priorities emerging from the data include modular furnishings, shaded/covered areas, accessible paths, reliable lighting and power, clear wayfinding, and provisions for water, toilets, and storage.Embedding preparedness features and multifunctionality across a network of neighborhood parks can strengthen community cohesion, speed emergency response, and transform ordinary public spaces into dependable nodes of urban resilience.
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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 | 0.001 | 0.002 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| 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".