Closing gender gaps through gender-responsive, demand-led breeding in Burundi
Bibliographic record
Abstract
Gender inequality persists in Burundi's agricultural sector, especially in the bean value chain dominated by women. Women often have less access to improved seeds and to productive technologies. Interventions dubbed "gender-responsive plant breeding" have been launched to develop new varieties to address the gender gaps in variety adoption. Gender responsive planting breeding in Burundi targets to develop bean varieties that respond better to gendered varietal and trait preferences. This paper provides a background of gender-responsive bean breeding in Burundi, documenting the methodologies that were used to integrate gender issues in bean breeding and socio-economic research. It also covers successes of gender-responsive breeding to date, primarily focusing the interdisciplinary teams that drove the process, development and release of varieties that incorporated traits favored by women and men actors. Evidence from surveys and value chain analysis reveal that gender-responsive breeding program increased the adoption of improved varieties by women and improved yields and productivity. The paper reveals that gender-responsive and demand-led bean breeding programs require stakeholders engagements to develop products that align with preferences of diverse actors at different nodes of the bean value chain.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".