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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

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.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

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