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Record W3090086957 · doi:10.1001/amajethics.2020.868

Using OCAP and IQ as Frameworks to Address a History of Trauma in Indigenous Health Research

2020· article· en· W3090086957 on OpenAlexaffabout
Angela Mashford‐Pringle, Kira Pavagadhi

Bibliographic record

VenueThe AMA Journal of Ethic · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsPublic Health Ontario
Fundersnot available
KeywordsIndigenousPossession (linguistics)Historical traumaColonialismCriminologyIndigenous cultureSociologyPolitical scienceLawGender studiesMedicineNursingEcology

Abstract

fetched live from OpenAlex

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.

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

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.130
metaresearch head score (Gemma)0.112
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.688

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1300.112
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0140.011
Science and technology studies0.0140.094
Scholarly communication0.0210.025
Open science0.0040.034
Research integrity0.0040.011
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.259
GPT teacher head0.472
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designTheoretical or conceptual
DomainMethods
GenreMethods

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".

Quick stats

Citations37
Published2020
Admission routes2
Has abstractyes

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