Access to ınformation and social solidarity in the 2023 Turkey earthquake: disaster education as citizenship education
Bibliographic record
Abstract
This qualitative study explores the experiences of 16 survivors of the 2023 earthquake in Turkey, aiming to highlight the critical role of disaster education within broader citizenship education. Through semi-structured interviews and inductive thematic analysis, four key themes emerged: access to information, trust in information sources, social solidarity, and the fulfillment of basic needs. These findings underscore the importance of integrating disaster education into citizenship education to empower individuals with the knowledge and skills necessary for effective disaster preparedness and response. The research advocates for multi-faceted approaches to disaster readiness that not only enhance immediate survival and recovery but also foster long-term community resilience. By amplifying the voices of earthquake survivors, this study contributes to a deeper understanding of the vital intersection between education, citizenship, and disaster management, offering insights into how to better equip citizens to respond to and recover from crises.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".