Machines That Cook or Women Who Cook? Lessons from Mali on Technology, Labor, and Women’s Things
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
By the last quarter of the twentieth century, grain mills had proliferated across rural Mali and were central to the story of women and development. Yet, proponents of such supposed labor-saving technologies often assumed that women in Africa have little technological experience or knowhow. The present article examines this well-worn narrative with an emphasis on the ways in which Malian women have interrogated different technological interventions from their own shifting perceptions. It is a history that predates the introduction of grain mills and post-colonial development and focuses on women's savvy when it came to assessing new technologies, especially in relation to cooking. This historical examination further illuminates not only women's concern for labor-saving technologies, but also women's ability to shape the infrastructure of their work. In so doing, they gender their tools as women's things and assert control over the meanings of their own work and status.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it