Study of the Characteristics of Farmers on Practicing Coping Strategies towards Household Food Security during Flood Period
Bibliographic record
Abstract
A study was carried out at flood affected reverine villages of three upazilas under Jamalpur district in Bangladesh during September, 2011 to May, 2012 to explore the relationship, contribution and direct–indirect effect between personal attributes and their coping strategies towards household food security practiced by the farmers during flood. Data were collected from randomly selected respondents through both the qualitative and quantitative techniques and analyzed with the help of SSPS. Out of 18 personal, economic, social and psychological characteristics of the farmers, the personal education, housing condition, annual income, annual expenditure, savings, organizational participation, participation in IGAs, cosmopoliteness, environmental awareness, knowledge on flood coping mechanisms and household food security had positive and credit received and utilization of received credit had negative while age, family size, training received, risk orientation and involvement in safety net programmes had no significant relation with coping strategies towards household food security during flood period.
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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 | 0.000 | 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".