A Remote Access Qualitative Study Protocol to Investigate the Coping Strategies in the Mindset of the Affected Adults after the 2025 Myanmar Earthquake
Bibliographic record
Abstract
On March 28, 2025, a 7.7-magnitude earthquake struck central Myanmar (GLIDE #EQ-2025-000043-MMR), compounding the country's existing political instability, economic fragility, and infrastructural weaknesses. Although seismic events have recurred throughout history, limited knowledge exists regarding how working-age adults (18-60), who play a central role in recovery, mobilize personal, cultural, and community resources to cope with adversity and reconstruct their lives. This is a protocol clarification for a remote access qualitative study using semi-structured interviews with 30 purposively sampled participants, half from heavily impacted zones (Sagaing, Mandalay) and half from nearby regions experiencing secondary disruption (Yangon). Using a remote system, interviews will be audio-recorded, transcribed verbatim, and analyzed thematically following Graneheim and Lundman's approach. This study aims to identify key coping strategies, including social support networks, spiritual practices, and local initiatives of working-age adults in Myanmar, and to compare how exposure severity shapes adaptive responses. Anticipated themes based on existing disaster and resilience literature include community-led resilience, hope through faith, and resource-sharing practices. Findings are expected to offer in-depth, culturally grounded insights that can inform disaster recovery programs, psychosocial support services, and policy frameworks aimed at strengthening resilience in Myanmar and similar low-resource, low-accessibility, crisis-affected settings.
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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 | 0.035 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.048 | 0.007 |
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".