Decades of Doing: Indigenous Women Academics Reflect on the Practices of Community-Based Health Research
Bibliographic record
Abstract
It has been several decades since the establishment of Ownership, Control, Access, and Possession (OCAP®) and the proliferation of work on Indigenous research ethics. Most of this dialogue emerged because of egregious health research practices in Indigenous communities and has since taken a foothold across all disciplines. Community-engaged research in Indigenous communities is challenging. It is important to reflect on some of the early ethical and methodological debates, which shape how we currently work with communities. This research describes the themes that emerged when two Indigenous scholars interviewed their Indigenous university-based colleagues who work in Indigenous health. These interviews uncovered four critical themes that were prominent and related specifically to understanding research ethics in Indigenous health research specifically. These themes included research in relationship, creating partnerships and negotiating across systems, self-determination applied to research, and community-engaged research.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchScience and technology studies Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | MetaresearchScience and technology studies Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | medium |
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 | 0.059 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.038 | 0.058 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.008 | 0.019 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".