Using OCAP and IQ as Frameworks to Address a History of Trauma in Indigenous Health Research
Bibliographic record
Abstract
Indigenous people have been studied at great length.To counter deficitbased research that can reinforce stereotypes, the National Aboriginal Health Organization introduced principles of ownership, control, access, and possession (OCAP ® ) to reduce historical trauma to individuals, families, and communities from research and reporting of findings.A further step in promoting culturally safe and responsible research with Indigenous peoples is to incorporate the Inuit Qaujimajatuqangit, traditional laws and principles that guide a way of life and of knowing.Based on these 2 guides, researchers and scholars should be working with Indigenous peoples to co-develop research rather than merely conducting research on Indigenous populations.By working collaboratively with researchers, Indigenous people can provide input to ensure that a project respects Indigenous culture, language, and knowledges and does not re-ignite or exacerbate historical trauma or further current colonial policies that marginalize and oppress Indigenous peoples.Research as Trauma Indigenous people in Canada have been the objects of colonial research that has harmed individuals and communities for generations.Much of this research was conducted without informed consent and with the investigators' knowledge that the research itself would put those involved in the study at serious risk.1,2,3 Problems with Indigenous health research are ongoing and extensive, including Indigenous people's forced participation; analysis, interpretation, and distribution of their data without their permission; and devaluation of their culture and erasure of colonialism's impact on their lived experience.2,4 Deficit-based research, which shows Indigenous groups in Canada comparing poorly to non-Indigenous Canadians, has directly harmed Indigenous individuals, families, communities, and nations.5 Such research has inflicted trauma on Indigenous people through physical injury, psychological distress, and cultural harm, in addition to creating distrust of research among larger communities affected by the research.6,7 Further maltreatment has been inflicted through researchers interpreting and using the resulting data in ways that can be misconstrued and that are problematic for the subjects of the research.Primary and secondary trauma that has resulted from The viewpoints expressed in this article are those of the author(s) and do not necessarily reflect the views and policies of the AMA.
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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 | 0.130 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.014 | 0.094 |
| Scholarly communication | 0.021 | 0.025 |
| Open science | 0.004 | 0.034 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".