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Record W2601377932 · doi:10.1177/1049732317697948

Enhancing Indigenous Health Promotion Research Through Two-Eyed Seeing: A Hermeneutic Relational Process

2017· article· en· W2601377932 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

VenueQualitative Health Research · 2017
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsDalhousie UniversityQueen's UniversityMcGill UniversityKahnawake Schools Diabetes Prevention Project
Fundersnot available
KeywordsIndigenousHermeneuticsPromotion (chess)Process (computing)SociologyHealth promotionWork (physics)Qualitative researchPublic relationsPsychologyEngineering ethicsNursingMedicineEpistemologyPolitical scienceSocial sciencePublic healthComputer scienceEngineeringPolitics

Abstract

fetched live from OpenAlex

The intention of this article is to demonstrate how Indigenous and allied health promotion researchers learned to work together through a process of Two-Eyed Seeing. This process was first introduced as a philosophical hermeneutic research project on diabetes prevention within an Indigenous community in Quebec Canada. We, as a research team, became aware that hermeneutics and the principles of Haudenosaunee decision making were characteristic of Two-Eyed Seeing. This article describes our experiences while working with each other. Our learning from these interactions emphasized the relational aspects needed to ensure that we became a highly functional research team while working together and becoming Two-Eyed Seeing partners.

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)0.122
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1220.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0480.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.009
Insufficient payload (model declined to judge)0.0000.002

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 head0.863
GPT teacher head0.763
Teacher spread0.100 · 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