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Record W251137095 · doi:10.18584/iipj.2015.6.2.4

Research as Cultural Renewal: Applying Two-Eyed Seeing in a Research Project about Cultural Interventions in First Nations Addictions Treatment

2015· article· en· W251137095 on OpenAlexafffundvenueabout
Laura Hall, Colleen Anne Dell, Barb Fornssler, C. A. Hopkins, Christopher J. Mushquash, Margo Rowan

Bibliographic record

VenueInternational Indigenous Policy Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health Research
KeywordsIndigenousDocumentationTraditional knowledgeSociologyProject teamPsychological interventionStorytellingCultural safetyPolitical sciencePublic relationsMedicineNursingManagementNarrativeEcology

Abstract

fetched live from OpenAlex

This article explores the application of two-eyed seeing in the first year of a three-year study about the effectiveness of cultural interventions in First Nations alcohol and drug treatment in Canada. Two-eyed seeing is recognized by Canada's major health research funder as a starting point for bringing together the strengths of Indigenous and Western ways of knowing. With the aim of developing a culture-based measurement tool, our team carried out an Indigenous-centred research process with our interpretation of two-eyed seeing as a guiding principle. This enabled us to engage in a decolonizing project that prioritized Indigenous methodologies and ways of knowing and knowledge alongside those of Western science. By concentrating on Indigenous governance in the research process, our project supported efforts at Indigenous cultural renewal. Two illustrations are offered, our team's reconceptualization of Western derived understandings of data collection through Indigenous storytelling and our research grant timeframe with Indigenous knowledge gardening. This article contributes to the Indigenous research and policy literature which is lacking documentation about how Indigenous communities and research teams are benefitting from two-eyed seeing.

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 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)0.008
metaresearch head score (Gemma)0.001
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 score0.765
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0150.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.342
GPT teacher head0.578
Teacher spread0.236 · 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 teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations90
Published2015
Admission routes4
Has abstractyes

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