“The farmer and her husband”: Engendering the curriculum in a Faculty of Agriculture in an Ethiopian university
Bibliographic record
Abstract
abstract This focus piece comes out of a recognition that higher institutions can and must play a key role in transforming the gendered landscape of food security. Close to 70% of labour related to post-harvest in Ethiopia is carried out by women. However, this does not mean that decision-making in a family (about what to grow or how to market it) is determined by women, and it also does not mean that women have equal access (compared to men) to resources and to status more broadly. Alongside this analysis is a recognition that women are often left out of the development of new technologies that could change the nature of their labour. While clearly there is a need to mainstream gender in the curriculum of post-harvest in higher education institutions, the unique challenges facing universities (especially in Agriculture) remains an area that is under-studied, even though within the development literature more generally the idea of mainstreaming and integrating gender has had prominence at least for severa...
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.029 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".