One indigenous academic's evolution: a personal narrative of native health research and competing ways of knowing
Bibliographic record
Abstract
Indigenous health research should reflect the needs and benefits of the participants and their community as well as academic and practitioner interests. The research relationship can be viewed as co-constructed by researchers, participants,and communities, but this nature often goes unrecognized because it is confined by the limits of Western epistemology. Dominant Western knowledge systems assume an objective reality or truth that does not support multiple or subjective realities, especially knowledge in which culture or context is important, such as in Indigenous ways of knowing. Alternatives and critiques of the current academic system of research could come from Native conceptualizations and philosophies, such as Indigenous ways of knowing and Indigenous protocols, which are increasingly becoming more prominent both Native and non-Native societies. This paper contains a narrative account by an Indigenous researcher of her personal experience of the significant events of her doctoral research, which examined the narratives of Native Canadian counselors’ understanding of traditional and contemporary mental health and healing. As a result of this narrative, it is understood that research with Indigenous communities requires a different paradigm than has been historically offered by academic researchers. Research methodologies employed in Native contexts must come from Indigenous values and philosophies for a number of important reasons and with consequences that impact both the practice of research itself and the general validity of research results. In conclusion, Indigenous ways of knowing can form a new basis for understanding contemporary health research with Indigenous peoples and contribute to the evolution of Indigenous academics and research methodologies in both Western academic and Native community contexts.
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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 | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.047 | 0.079 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.012 |
| 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".