The Role of Social Capital in Rural Household Food Security: The Case Study of Dowa and Lilongwe Districts in Central Malawi
Bibliographic record
Abstract
<p>This paper explores the contribution of social capital on the rural household food security. Social capital is the ability of community actors to secure benefits by virtue of membership in social networks or other structures. In the past decade, consensus has emerged among scholars and practitioners of development that social capital can contribute significantly to the alleviation of poverty. Food insecurity is an indicator of poverty. This paper therefore takes this view by investigating the impact of social capital on the food security situation of rural people in developing countries, using the case study of Malawi in Sub-Saharan Africa. Using household survey data different social capital variables were incorporated into the household social welfare model, controlled by human capital, physical capital, household and geographical characteristics in order to test the linkage between social capital and rural household food security situation in the context of a developing country. Household food security status was improved by membership to farmers’ organizations, household network size and engagement in voluntary activities. When all social capital variables were incorporated into the model the explanatory power of the model improved by 20% on household food security.</p><p>We conclude that social capital has positive influence on household food security; however, the effects vary depending on the nature of social capital. The results indicate the significance of social networks in improving the socio-economic livelihoods of the people in rural areas in developing countries.</p>
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".