A journey of partnership: Supporting Indigenous science in Western, colonial-grounded academic institutions
Bibliographic record
Abstract
INTRODUCTION: Engagement of Indigenous science (Indigenous research, knowledges, and processes) is increasingly recognized within institutions of higher learning, funding bodies, and publication outlets. Respectful and authentic support for Indigenous science requires transformations of Western, colonial-grounded knowledge and knowledge processes, bodies, and institutions to meaningfully and appropriately include Indigenous ways of knowing, being, and doing. OBJECTIVE: The objective of this study was to identify fundamental changes required to support Indigenous science within Western, colonial-grounded academic institutions focusing on "Identity and Colonial Institutions". METHODS: In 2019, a three-day gathering of 18 Indigenous and non-Indigenous researchers and trainees, Elder/knowledge helper/knowledge keepers, and community members was held in Treaty 1 territory and birthplace of the Métis Nation. Through talking circles, participants shared their experiences working with Indigenous communities on projects involving Indigenous knowledges. RESULTS: Thematic analysis drew meaning from the talking circles, identifying four main themes: 1) Building Bridges; 2) Institutional Practice; 3) Original Knowledges; and 4) Multifaceted Identity. Focusing on "Identity and Colonial Institutions" stemming from these themes, recommendations for supporting Indigenous science were identified around four central actions: 1) Embedding respectful and authentic support; 2) Acceptance, endorsement, incorporation, and education among the broader research community; 3) Prioritizing and valuing Indigenous research, knowledges, processes, and contributions; and 4) Privileging of multiple worldviews. CONCLUSIONS: Institutions, funding agencies, journals, and all individuals, organizations, and entities involved in research are encouraged to enact these recommendations and take action to support Indigenous science.
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 | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.021 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.003 | 0.032 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".