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Record W2737666726 · doi:10.1177/1609406917704095

Meaningful Engagement of Indigenous Youth in PAR

2017· article· en· W2737666726 on OpenAlexafffundabout
Linda Liebenberg, Arnold Sylliboy, Doreen Davis-Ward, Amber Vincent

Bibliographic record

VenueInternational Journal of Qualitative Methods · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsGovernment of NunavutDalhousie University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFlexibility (engineering)IndigenousProcess (computing)Public relationsCommunity engagementYouth engagementParticipatory action researchAdaptabilityService providerCitizen journalismPsychologyService (business)Mental healthSociologyBusinessPolitical scienceMarketingComputer science

Abstract

fetched live from OpenAlex

This article presents the process used in a Participatory Research Project with Canadian Indigenous youth aimed at understanding their civic and cultural engagement. Specifically, we reflect on the approach taken, together with the core role of community partners in facilitating youth participation in this project. The process we used had three key aspects which facilitated effective youth engagement. First was flexibility and adaptability of the original study design, allowing the young people to adjust the project design, increasing their comfort levels and in doing so, assume as much or as little ownership of the process as they wanted. Second was building on preexisting relationships between mental health service provider staff and the community, which accelerated the establishment of trust. Through this trust, new relationships within the research team were able to develop. Third was the support of the youth engagement by the service provider staff, which provided support as required. This process improved the quality of the data collected, related findings, and for effective dissemination. Importantly, this staff–youth interaction has also increased longevity of the dissemination process. Our intent in reflecting on this process here is to further the dialogue on how to meaningfully engage ordinarily silenced and/or marginalized youth in research and evaluation as well as the sharing of findings.

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)0.016
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.712
GPT teacher head0.668
Teacher spread0.044 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations38
Published2017
Admission routes3
Has abstractyes

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