Bibliographic record
Abstract
As anthropologists interested in applying our research to the improvement of health and quality of life, we often find ourselves in places rife with poverty, violence and environmental degradationnot to mention corruption, scandal and controversy. This can make our job not only heartbreaking, but difficult to carry out. This paper briefly addresses how the selection of a fieldsite for ethnographic research should be based on more than local health issues alone. Failure to make a careful consideration of broader factors that contribute to the focus of one's study can interfere with the success of research. I discuss two field experiences to illustrate this point. The first is research that I attempted to carry out in Chiapas, Mexico. The second example is from research conducted in Zimbabwe. Both projects involved traditional medicine and a great deal of controversy. Only one was successful. The ultimate goal of my work in Chiapas was to contribute to a more detailed picture of indigenous environmental knowledge by characterizing the relationship between Mayan perceptions of the medicinal plants they ingest and perceptions held by scientists who study these plants in a laboratory. More specifically, my research was designed to answer the question: Do the Tzeltal Maya share folk models of medicinal plant actions and do these models reflect the biological activities of compounds found in such plants? I planned to work in the Tzeltal community of Ch'ixaltontik, which is a tiny hamlet in the municipality of Tenejapa. The idea was to elicit folk models of medicinal action for a set of common medicinal plants that could be compared with the scientific literature. I was awarded a grant from the National Science Foundation to do this research. I also received some funding from the Maya International Collaborative Biodiversity Group (Maya ICBG)2 project to translate my findings into Tzeltal. Translating my data and results into Tzeltal would have helped the people of Ch'ixaltontik make claims to their intellectual property and give them leverage to determine what kind of medicinal plant research may take place in their community. The controversy in this case has to do with the politics of medicinal plant research in Highland Chiapas. Drs. Brent and Elois Ann Berlin and their students have studied Mayan medicinal plants in the region for over 20 years. Unfortunately, their most recent project-the Maya ICBG-caused a torrent of argument and misunderstanding. The Maya ICBG was supposed to be a five-year project that would study Maya ethnomedicine, inventory the flora of Highland Chiapas and screen common medicinal plants for biological activities. The project was also designed to develop sustainable, culturally appropriate income-generating opportunities for the Maya. Finally, it was intended to be a model for doing ethnobotanical drug discovery fairly. That is, with the explicit aim of sharing benefits equally with indigenous communities. The drug discovery portion of the project attracted the attention of human rights groups who assumed that because the project was funded by the American government it had to be another example of corporate interests out to exploit indigenous people. When the regional Mayan traditional healers association (known by the acronyms OMIECH and COMPITCH) publicly protested the Maya ICBG, activists from the United States and Canada (led by the now defunct Rural Advancement Foundation International) rushed to their aid. The healers, with the help and encouragement of these activists, accused the Maya ICBG of stealing their specialist medical knowledge. It did not seem to matter that the Berlins were interested in the medical knowledge of everyday people and had the unanimous support of numerous Mayan communities in the region. Neither the activists nor the healers cared that the researchers had convinced their corporate partner to give a quarter of all potential profits to the highland Maya and developed means to equitably distribute these profits throughout the region. …
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".