Assessing the Determinants of Food Security Status in Bangladesh: A Micro-Econometric Analysis
Bibliographic record
Abstract
Food security is an intricate issue which includes diverse aspects as well as many linkages. In Bangladesh, food security is tried to be achieved by increasing the production of rice both by employing modern agricultural technology as well as by increasing the area under rice production. Despite the impressive gains in increasing domestic food grain production, problems of food and nutrition security still remain. Bangladesh is yet to achieve comprehensive food security that resolves the problems of inadequate food intake and chronic malnutrition among those who are poor and vulnerable. The main objective of this paper is to the contribution of different factors behind household food security status of 180 households in three Northern districts of Bangladesh. The study area was chosen because relatively little energy consumption data are available concerning this geographical area. The study used both primary and secondary data. Food security status of each household was assessed on the basis of the food security line using the daily calorie intake recommended by FAO. This method has proven to be efficient in measuring food security at household level. Additionally, the use of a logistic regression model identified the factors that plays crucial role in determining the food security status of the households. Results from the food security index revealed that more than 60 percent of households were with food insecurity. In addition, we found that total monthly household income, age of household head, education level of household head, household size, farm size, gender of household head, livestock ownership and quantity of cereal production had significant influence on food security status at the household level.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".