Toward more ethical engagements between Western and Indigenous sciences
Bibliographic record
Abstract
There is growing interest among Western-trained scientists in engaging with Indigenous sciences. This interest has arisen in response to social pressures to reckon with the colonial foundations of Western science and decentre Western ways of knowing, as well as recognition of the need to draw upon the gifts of multiple knowledge systems to address today's many complex social and ecological challenges. However, colonial patterns and power relations are often reproduced at the interface between Western and Indigenous sciences, including the reproduction of epistemic Eurocentrism and extractive modes of relationship between settlers and Indigenous Peoples. This paper seeks to support Western-trained scientists to recognize and interrupt these patterns in order to create the conditions for more ethical, respectful, and reciprocal engagements with Indigenous sciences. We also offer a map of the different ways that Western sciences have thus far engaged Indigenous sciences. We particularly highlight the emergent possibilities offered by a reparative approach to engagement that emphasizes the responsibility of Western science to enact material and relational repair for historical and ongoing harm, including by supporting Indigenous self-determination and sovereignty in science and beyond.
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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 | 0.083 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.102 |
| Scholarly communication | 0.022 | 0.018 |
| Open science | 0.002 | 0.035 |
| Research integrity | 0.008 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 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".