Intersections of Ethics of Indigenous Health Research and Health Research Education.
Bibliographic record
Abstract
Health research involving Indigenous peoples is regulated by guidelines based on the ethics of Indigenous health research, which establish routes to knowledge development in order to support and improve health for Indigenous communities. Despite these guidelines, health imbalances remain and continue to negatively impact Indigenous peoples. This thesis explores some of the barriers and strengths of ethical guidelines of Indigenous health research in Canada. Using a community-based approach, this research shifts the focus away from a study of Indigenous peoples themselves, to a study of the practices that health researchers employ when conducting health research involving Indigenous peoples. An online survey was developed and distributed via email and through social networks to health researchers who work in the field of Indigenous health research. The survey consisted of 22 questions using and a Likert scale (Likert, 1932) to explore perceptions of ethical guidelines in use by researchers who engage in Indigenous health research. After data quality control analysis, 228 respondents were considered valid and constituted the data set. Results suggest a general level of agreement (Somewhat Agree) with the value of the health ethical guidelines used by researchers. High agreement was found for basic items such as ethical guidelines being easy to access and the amount of information offered was appropriate. However, low agreement was found on items that rated the perceived characteristics of ethical guidelines: their clarity, and whether they reflected the current social context of Indigenous peoples; the inclusion of Indigenous paradigms inside ethical guidelines and whether the guidelines enhanced health researchers’ understanding of Indigenous worldviews. Resultsalso describe some other characteristics of Indigenous health research, such as exploring who is researching what, when, and how with special attention to research methodologies, approaches and perceived engagement with Indigenous communities. A major implication of these results suggests the need for the inclusion of Indigenous research perspectives in health research and health research education much more broadly if they are to effectively support Indigenous healthier 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 | 0.123 | 0.090 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.018 | 0.165 |
| Scholarly communication | 0.022 | 0.010 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.006 | 0.010 |
| 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".