Sweet Success? Interrogating Nutritionism in Biofortified Sweet Potato Promotion in Mwasonga, Tanzania
Bibliographic record
Abstract
This thesis is an ethnographic study of the promotion of biofortification, and specifically biofortified sweet potato (OFSP) as a solution to malnutrition in the Mwanza region of Tanzania, a major sweet potato producing area in the country.Through a feminist lens, I examine sweet potato, commonly considered a 'women's crop' in Tanzania, and the campaign to promote its use as entry-points to analyze the intersection between women's dynamic engagement in food-related labour and the gendered, economic and social conditions in which women sweet potato farmers' livelihoods are situated.Funded by private foundations and international agricultural research centres, biofortified sweet potato campaigns targeted thousands of women farmers in several Sub-Saharan African countries to address malnutrition by increasing the nutrient content of staple, subsistence crops such as sweet potato.My findings show that OFSP promotion reinforced existing normative gendered food production roles as well as scientific, technical interpretations of nutrition, while disregarding how socio-economic and environmental conditions mediate every day and seasonal dietary practices.A close examination of the research activities and marketing of biofortified sweet potato reveal the inherent gendered and social inequalities embedded in current strategies to address nutrition in agricultural development programs in Tanzania.My research suggests that women's associated labour and varying perceptions of nutrition were under-acknowledged in such campaigns.Analysis of discursive and material networks embedded in OFSP campaigns revealed both the intended and unintended long-term and seasonal, social, economic, health and environmental implications of these campaigns and their oversights on sweet potato producers in Mwasongwe village since 2006.As a result, OFSP benefits to the female sweet potato producers in my study remained short-term, uncertain, and dependent on external financing and international partnerships, and on individual farmers' access to economic, social and environmental assets.This thesis could not have been possible without the generosity and kindness of the numerous collaborators with whom I spent many months in Tanzania.In Mwanza, I am indebted to the residents of Mwasongwe village, members of Imala Gihabu, the technical and science staff at Ukiriguru institute and the regional staff at Helen Keller International and the Tanzania Home Economics Association (TAHEA).Stephen and Loyce Veryser not only provided me with accommodation during my fieldwork, but also insightful evening discussions.In Arusha, invaluable logistical support offered by my Farm Radio International family allowed me to smoothly set up and carry out the fieldwork.My research partner, Anna Bayona, accompanied me every day into the field.Through her openness and kindness, she allowed for lively and engaging interactions with the diverse range of residents in the region.Dr. Rose Shayo at the University of Dar Es Salaam offered initial contextual understanding and entrance into the research community in Tanzania.Dr. Regina Kapinga assisted me in selecting my field site.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".