The gendered value chain of matooke banana and its implications for tissue culture adoption in Uganda
Bibliographic record
Abstract
Tissue culture banana is promoted as a form of micro-propagation that can aid farmers in managing pests and disease in Uganda, the country with the largest per capita consumption of banana in the world. But uptake amongst smallholder farmers remains low. This study recruited 71 farmers from five banana-growing districts in Uganda to assess how gender dynamics of matooke production impact the adoption and sustained use of tissue culture. We collaborated with farmers and co-produced a three-stage, participatory methodological protocol for mapping value chains. Our analysis reveals a gendered division of labour and limited access to resources that shape farmers’ ability to benefit from this technology. Women farmers are interested in tissue culture banana but face challenges related to demands for land preparation, accessing plantlets, and relevant knowledge, while men are more reluctant due to their fragility, high cost, and the additional labour demands needed to ensure the crop's survival. This study highlights the necessity of understanding the gendered division along a crop’s value chain to ensure the success of new breeding technologies.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".