Co-managed research: non-Indigenous thoughts on an Indigenous toponymy project in northern British Columbia
Bibliographic record
Abstract
This paper reflects on the methodological challenges of co-managed research as experienced from a non-Indigenous perspective. In 2003, Tl'azt'en Nation and the authors initiated a toponymy study that involved finding a curricular use for Dakelh place names. In this article, we chronicle our experiences with negotiating and managing this study with Tl'azt'en Nation. Some events are specific to the topic; others are characteristic of co-managed research in general. We offer insights into what it means as non-Indigenous researchers to enter discursive territory that is charged with emotion and cultural sensitivity, and also explore the often contentious issues that can arise in Indigenous research, particularly oral history, ethnohistorical interpretation, and cultural representation. The paper concludes by discussing the opportunities and challenges of co-managed 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 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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.070 | 0.036 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".