Womens empowerment: A gender outcome of an improved agriculture health and nutrition project in Zambia and Malawi
Bibliographic record
Abstract
HIV Aids has had a major impact on resource-limited African rural Sub-Saharan communities, especially upon women who typically experience greater gender inequity, have fewer assets and greater food insecurity and vulnerability. Coordinated interventions in crop productivity, nutrition, AIDS treatment, and livelihood security can have significant positive impacts on individuals and households; however their impact upon gender relations and social equity is unclear. Qualitative interviews and an integrative model of factors influencing women’s empowerment are used to examine this issue in four villages of the Miracle Project in Zambia and Malawi. Although some local agency and NGO programs existed in these villages prior to project inception, female respondents reported improvements in crop productivity and income, some initiation of new enterprises, improvement in ownership of assets and housing quality and access or re- access to kinship or community based mutual assistance networks from which they had been excluded. Consumption of the introduced quality protein maize and products from home processing of soyabeans were cited as improving household nutrition. Together with increased accessibility to retroviral drugs, women’s health has improved; levels of poverty and stigmatisation have reduced and allowed many to display an improved degree of empowerment. Key words: HIV/AIDS; nutrition; agriculture; gender; social inclusion; empowerment.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".