Exploring Household Preparedness towards Earthquakes along the East African Rift Systems in Tanzania: A Case of the Bukoba Municipality
Bibliographic record
Abstract
Tanzanian households in the East African Rift System (EARS) are susceptible to regular earthquake shocks, but it is uncertain how they are prepared to handle the consequences. Residents of Bukoba Municipality are particularly at risk because of its location along the EARS, rapid population growth, and encroachment of earthquake fault zones. This study was conducted in the Kashai and Hamugembe wards of the municipality to examine household readiness for potential earthquakes. A mixed-methods approach was used, gathering data from 391 respondents, 8 key informants, and 12 focus group participants through a questionnaire survey, interviews, focus group discussions (FGD), and physical visits. Qualitative and quantitative data were analysed using content and descriptive statistics, respectively. The findings revealed that most respondents were unaware of the cause of earthquakes and safety measures. The dominant earthquake skill in the study area was evacuation (58.3%). Furthermore, 86.2% of respondents lived in unreinforced buildings, water was the most reserved emergency item (39.4%), and mobile phones were prevalent (96.2%) means of communication and information. We also found that neighbour contacts were the most (91.8%) emergency number respondents had. The limited knowledge and skills, lack of emergency items, and unreinforced buildings indicate that residents are at significant earthquake risk. However, the widespread use of mobile phones presents an opportunity for effective knowledge dissemination. We recommend investing in public earthquake awareness programmes and using multimedia to disseminate earthquake information. Additionally, the government should implement earthquake-resistant construction regulations and improve communication among local communities and first responders.
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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 | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".