“Remember the women of Osiri”: women and gender in artisanal and small-scale mining in Migori County, Kenya
Bibliographic record
Abstract
In this paper, we explore women’s livelihoods and the operation of gender norms and structures in the Osiri artisanal gold mining area in western Kenya. While “women” and “gender” are seen as increasingly important to policy frameworks for developing mineral resources on the African continent, understandings of women’s roles in artisanal and small-scale mining, and of the importance of gender in structuring those livelihoods, remain limited. Drawing on field research conducted from 2014 to 2018, we demonstrate that while gender norms and structures operate to delimit women’s mining roles, in daily encounters women and men navigate, resist and sometimes reframe those norms. Further, we explore how gender norms may not impact all women the same and how other social variables, such as age, may also influence how women navigate their mining livelihoods.
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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) | 0.001 | 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".