Indigenous knowledge data management issues and co-production of knowledge in Kamchatka
Bibliographic record
Abstract
This review analyzes content from various sources, including international projects, academic research, and government-supported programs that focus on the traditional knowledge of the Indigenous peoples in Kamchatka. Indigenous communities in Kamchatka have actively participated in research since the early 2000s, collaborating with scientists on various initiatives. This review examines conservation and research projects involving Kamchatka's Indigenous peoples, emphasizing the use of Indigenous and co-produced knowledge for the mutual benefit of both the Indigenous communities and the scientific community. This review is based on four case studies and explores the challenges and opportunities revealed through previous research, along with the insights gained from these experiences. Additionally, this paper takes the opportunity to reassess and discuss the potential restructuring of research practices in Kamchatka, addressing the persistent inequalities in resources and power that affect collaborative scholarship. This reassessment could pave the way for a new chapter in collective scholarship, which will be valuable for future collaborative efforts and Indigenous-led research.
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 | 0.003 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".