Bibliographic record
Abstract
Purpose The purpose of this paper is to address some of the implications for methodology and ethics that arise when researchers in Indigenous territories locate their research projects as taking place within Indigenous countries. Centering the argument that ethical research with Indigenous communities must be rooted in upholding the primacy of Indigenous sovereignty, numerous considerations to improve qualitative research practices in Indigenous countries are discussed. Design/methodology/approach The author starts by introducing his relationship to Indigenous research as a mixed-Indigenous researcher. Moving onto discussing preliminary research considerations for working in Indigenous territories, the author argues that qualitative researchers must become familiarized with the historical and geographical contexts of the Indigenous countries they plan on working in. Using Canadian history as an example, the author argues that settler-colonial nationalisms continue to attempt to erase and replace Indigenous countries both in historical and geographical narratives. Building on Indigenous literature, the author then outlines the necessity of being aware of nation-specific protocols in law, culture, and knowledge production. Findings Drawing on this discussion, the author proposes a framework for preliminary research that can be used by qualitative researchers looking to ensure their projects are grounded in the best practices for the specific Indigenous countries they want to work with. Originality/value The author concludes that researchers should not expect Indigenous knowledge keepers to contribute large amounts of labour towards debunking colonial mythology and proving the existence of Indigenous countries. By doing this work as part of the preliminary research process, researchers create space for better collaborations with Indigenous communities.
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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 | 0.093 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.030 | 0.100 |
| Scholarly communication | 0.020 | 0.023 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".