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Record W3191791238 · doi:10.46743/2160-3715/2021.3835

The Importance of Explicit and Timely Knowledge Exchange Practices Stemming from Research with Indigenous Families

2021· article· en· W3191791238 on OpenAlexafffundabout
Elizabeth Cooper, S. Michelle Driedger

Bibliographic record

VenueThe Qualitative Report · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of ManitobaUniversity of Regina
FundersCanadian Institutes of Health ResearchUniversity of TorontoSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsMetisIndigenousParticipatory action researchGeneral partnershipCitizen journalismPublic relationsCommunity-based participatory researchPsychologyProcess (computing)SociologyTraditional knowledgeMedical educationPolitical scienceMedicineComputer scienceLaw

Abstract

fetched live from OpenAlex

Ethical research practice within community-based research involves many dimensions, including a commitment to return results to participants in a timely and accessible fashion. Often, current Indigenous community-based research is driven by a partnership model; however, dissemination of findings may not always follow this approach. As a result, products may not be as useful to participants who were motivated to be involved in the research process. We conducted a seven-week workshop on three occasions with different First Nations and Metis women and girls (age 8-12) in Winnipeg, Manitoba. The workshop explored participants’ perspectives around health, safety, and family wellbeing using a strength-based, participatory approach. Participants noted that a key challenge they face when interacting with researchers, policy makers, and program staff is the lack of tailored dissemination materials. Returning results in a format that meets the expressed desire of participants is an ethical necessity to ensure that research is not perpetuating past colonial practices. Doing so quickly and with meaningful content requires careful execution and consideration, especially when working within intergenerational contexts. We describe in this paper how results were returned to families in an accessible way outlining the role that integrated knowledge exchange can play in the process of healing.

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)0.014
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.660
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0080.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.252
GPT teacher head0.543
Teacher spread0.292 · 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

Citations3
Published2021
Admission routes3
Has abstractyes

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