Medicinal Plant Use Influenced by Health Care Service in Mestizo and Indigenous Villages in the Peruvian Amazon
Bibliographic record
Abstract
Medicinal plants, as a type of non-timber forests (NTFP), have been expected to support the livelihoods of people globally, especially in rural and forest areas in developing nations. As medicinal plants occupy a unique position, with direct repercussions for people’s health and as a potential income resource, it is necessary to take the interaction with, and influence of, modern medicine into account when they are considered as a NTFP. This study pursued the influence of the health care service on medicinal plant utilization in mestizo and indigenous villages near secondary population agglomerations in the Peruvian Amazon. The study found some influence of the health care services on medicinal plant use in the study site, indicating that 1) medicinal plants are not necessarily a highly dependable approach for health care, 2) there are insufficient conditions for the development of a commercial market for medicinal plants, and 3) mestizo and indigenous households have similar health care utilization behaviours, although indigenous households are more affected by modern medicine, especially health care insurance, than the mestizo households. The health care service is an important factor for medicinal plant use for both health and livelihood. Without considering this factor, the potential of medicinal plants as NTFP cannot be fully understood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| 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".