Bibliographic record
Abstract
Hmong ethnic minority populations in Vietnam’s northern borderlands have a long history of oral tradition and story-telling. Yet with an historical absence of literacy and no self-created written archives, the first-hand knowledge and experiences of Hmong elders is seldom communicated beyond their kin. At the request of a Hmong community member we developed a collaborative, intergenerational oral history project that would allow stories of Hmong elders to be shared on the internet. Concurrently, we trained Hmong youth in research methods, helping to improve their English skills and contribute to inter-generational knowledge transfer. Drawing on debates regarding collaborative North-South ethnography, positionality and critical reflexivity, and feminist fieldwork approaches, we contemplate our roles as two Global North researchers interacting with Global South ethnic minority youth and elders, and the degree to which we were able to help support the creation of subaltern counter-narratives to Vietnamese state discourses of upland minority histories.’
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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 | 0.000 | 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 | 0.002 | 0.001 |
| 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".