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Record W2889960802 · doi:10.18584/iipj.2018.9.4.1

The Path of Creating Co-Researchers in the File Hills Qu'Appelle Tribal Council

2018· article· en· W2889960802 on OpenAlexaffvenueabout
Jessica Dieter, Lauren T McKim, Jenna Tickell, Carrie Bourassa, Jaime Lavallee, Gail Boehme

Bibliographic record

VenueInternational Indigenous Policy Journal · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsHealth Sciences North
Fundersnot available
KeywordsParticipatory action researchIndigenousCommunity-based participatory researchCulturally appropriateBest practiceTraditional knowledgeKnowledge translationCitizen journalismSociologyCulturally sensitivePublic relationsPolitical scienceMedicinePsychologyGerontologyAnthropologyKnowledge managementLaw

Abstract

fetched live from OpenAlex

Currently, there is a need for implementing ethical, culturally safe practices when engaging in research with Indigenous communities. As a result, best practices in culturally-safe Indigenous health research have been created to mitigate the existing barriers in health and health research stemming from Canada’s colonial history. This article includes a brief examination of those best practices, including community-based participatory research, OCAP® principles, knowledge translation, and positioning communities as co-researchers. Furthermore, it provides an overview of a community-based research project that examines community members’ knowledge of and experiences with dementia. The central themes that emerged during this project are also discussed, reaffirming the need for a culturally safe dementia research model in Indigenous communities.

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)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.164
GPT teacher head0.472
Teacher spread0.308 · 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

Citations14
Published2018
Admission routes3
Has abstractyes

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