On Using Expert-Based Science to 'Test' Local Ecological Knowledge: A response to: Gilchrist et al. 2005. 'Can Local Ecological Knowledge Contribute to Wildlife Management? Case Studies of Migratory Birds'
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
"The challenges and opportunities of incorporating information collected through scientific studies with the experience-based knowledge of resource dependent communities have been the focus of numerous studies. However, there are relatively few examples in which ecological science and local knowledge have both been successfully incorporated to provide meaningful input into resource management. In their recent article in Ecology and Society, Gilchrist et al. provide a thorough evaluation of Local Ecological Knowledge (LEK) using expert-based ecological studies often referred to as 'western science.' Although we applaud their recognition of the value of and desire to promote LEK, it is unfortunate that they use expert-based ecological data as a 'test' to determine the 'reliability' of LEK. Even though the authors indicate their wish to use the two different approaches to identify 'constraints and limitations of both approaches,' they fail to discuss the assumptions, limitations, or constraints of the ecological studies that they use. We do not take issue with their ecological studies; we presume they are of the highest quality. However, to assume that the ecological studies are error free and without any bias or limitation is perhaps somewhat misguided, albeit an assumption that many scientists still make. Indeed, Freeman (1992) provides examples in which conflicts occurred in the Canadian Arctic between LEK and expert-based science over aerial surveys of bowhead whales in the Beaufort Sea and caribou in what is now Nunavut, where local perceptions of the state of these wildlife populations were initially considered 'unreliable' but were resolved when biases in ecological studies were corrected using local knowledge. These case studies illustrate the limitations of ecological research and monitoring, and provide a cautionary tale against accepting them as 'truth.'"
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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 it