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Record W1555145387

Community-based sport research with Indigenous youth.

2015· article· es· W1555145387 on OpenAlexaboutno aff
Tara-Leigh McHugh, Nicholas L. Holt, Chris Andersen

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2015
Typearticle
Languagees
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoiceIndigenousParticipatory action researchCommunity-based participatory researchQualitative researchSociologyPublic relationsCitizen journalismPolitical scienceSocial scienceEconomic growthAnthropologyEcology
DOInot available

Abstract

fetched live from OpenAlex

There is critical need to better understand how to enhance sport participation among Indigenous youth and how to provide sporting\nopportunities in ways that contribute positively to health and wellness. The purpose of this paper is to describe our attempts to �deeply engage�\nIndigenous youth in sport research via a community-based participatory research (CBPR) approach. Specifically, we describe how a range of qualitative\ndata generation techniques have been used in our research, that is focused on exploring how communities can support sport opportunities for Indigenous\nyouth in Edmonton, Alberta. Our program of research, which included the use of one-on-one interviews, sharing circles, and photovoice, provides\ndirection for utilizing collaborative research approaches that respect Indigenous youth as equal partners in sport research. Furthermore, findings from\nour research have provided in-depth insights into the experiences and meanings of sport for Indigenous youth, and contributed to furthering\nunderstandings of the necessary processes that are foundational to engaging in relevant and respectful sport research with Indigenous youth

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)0.010
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.288
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.002
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.080
GPT teacher head0.346
Teacher spread0.266 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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