Researcher as learner, participants as knowers: an ethnographic snapshot of women sharing knowledge in a rural Uganda community
Bibliographic record
Abstract
This snapshot ethnographic research was conducted in Kihande Village in Uganda with the Agabagaya Women’s Group for a period of five weeks in 2004. Using a feminist ethnographic methodology, the researcher explores how women value, share and pursue knowledge informally among themselves to support themselves, their families and their communities. The analysis indicates that the women of Agabagaya are knowers in their worlds, that they actively pursue educational opportunities and development opportunities, and that they do so from a grassroots level. This particular group does not rely on and may actually be hindered by external development organizations and outside educational influences with top-down models. However, the group does use external development agencies when there is opportunity for the group to benefit. The researcher further explores the positions and implications of a white, Western researcher conducting research in a developing, non-white country and discovers that positive and respectful relationships are at the heart of the research process and that the participants control many aspects of the research itself.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".