Learning from Both Sides: Experiences and Opportunities in the Investigation of Australian Aboriginal Medicinal Plants
Bibliographic record
Abstract
With one of the oldest surviving cultures in the world, Australian Aboriginal people have developed immense knowledge about the diverse Australian flora. Western scientific investigation of some Australian Aboriginal medicinal plants has demonstrated interesting pharmacological activities and chemistry, however the majority of these species have not yet been extensively examined. We argue that research that is locally initiated and driven by Indigenous traditional owners in collaboration with Western scientists has significant potential to develop new plant-based products. Locally driven medicinal plants research in which traditional owners work as researchers in collaboration with University-based colleagues in the investigation of medicines rather than "stakeholders" or "informants" is one model that may be used in characterising plants with the potential to be developed into sustainable plant-based medicinal products with commercial value. Our team has taken this approach in research located both on traditional homelands and in the laboratory. Research being conducted by the University of South Australia and Chuulangun Aboriginal Corporation has led to patent filing for protection of intellectual property associated with novel compounds and extracts with the potential for development through cosmetic, complementary medicine and pharmaceutical routes. Ongoing research is examining the commercial developmental pathways and requirements for product development in these spaces. This review will address the opportunities that might exist for working in partnership with Australian Indigenous communities, some of the scientific knowledge which has been generated so far from our work together and the lessons learnt since the inception of the collaboration between the Chuulangun Aboriginal Corporation and scientists from the University of South Australia.
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 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 | 0.012 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.017 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".