Indigenous works and two eyed seeing: mapping the case for indigenous-led research
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore Indigenous Works’ efforts to facilitate Indigenous-led research that is responsive to the socio-economic needs, values and traditions of Indigenous communities. Design/methodology/approach This paper is grounded in an Indigenous research paradigm that is facilitated by Indigenous-led community-based participatory action research (PAR) methodology informed by the Two Row Wampum and Two-Eyed Seeing framework to bridge Indigenous science and knowledge systems with western ones. Findings The findings point to the need for greater focus on how Indigenous and western knowledge may be aligned within the methodological content domain while tackling a wide array of Indigenous research goals that involve non-Indigenous allies. Originality/value This paper addresses the need to develop insights and understandings into how to develop a safe, ethical space for Indigenous-led trans-disciplinary and multi-community collaborative research partnerships that contribute to community self-governance and well-being.
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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 | 0.047 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.042 | 0.069 |
| Scholarly communication | 0.021 | 0.017 |
| Open science | 0.005 | 0.026 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 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".