Does Knowledge about Earthquake Vary with Respondent’s Socio-Demographic Dimensions? A Study in Sylhet City of Bangladesh
Bibliographic record
Abstract
The prime and foremost purpose of this study was to explore climate change perception among indigenous people living in Sylhet, Bangladesh. This study also tried to investigate the nexus between some socio-demographic dimensions of the respondents and their perception regarding climate change. The present study followed descriptive-explanative research design where survey method used to collect necessary data. In case of survey method, a self-developed semi structured questionnaire was provided to the respondents for collecting relevant data. Total number of population was 75 and 63 respondents has been interviewed following the sample size estimation of Nurul Islam (2011). Findings of this study revealed that, there is a statistically significant difference between some socio-demographic dimensions (like; Age, Family type, Education and Income) and climate change perception. Furthermore, no statistically significant relationship found between Gender, Religion, Savings and climate c...
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".