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Record W1889130846 · doi:10.1080/0145935x.2014.962132

Youth-Guided Youth Engagement: Participatory Action Research (PAR) With High-Risk, Marginalized Youth

2015· article· en· W1889130846 on OpenAlexaff
Yoshitaka Iwasaki, Jane Springett, Pushpanjali Dashora, Anne-Marie McLaughlin, Tara-Leigh McHugh, Youth Yeg Team

Bibliographic record

VenueChild & Youth Services · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsPositive Youth DevelopmentYouth studiesParticipatory action researchDistrustYouth participationYouth engagementSociologyPhotovoiceAction (physics)Citizen journalismPublic relationsCivic engagementPsychologyPolitical scienceDevelopmental psychologyGender studiesEconomic growth

Abstract

fetched live from OpenAlex

Engaging youth who live with high-risk, marginalized conditions presents a significant challenge in our society, considering the prevalence of disconnect and distrust they often experience within their social environments/systems. Yet, meaningful youth engagement is a key concept not only for youth development, but also for a systems change to more effectively support high-risk youth and families. This article presents a framework of youth engagement developed over 9 months, using participatory action research (PAR) with 16 youth leaders in a community-based research team. Although this framework has incorporated the youth leaders’ lived experiences, talents, and voices, positive youth development (PYD) and social justice youth development (SJYD) have theoretically contextualized our research. Youth leaders guided the framework's development, including the identification of key themes/dimensions, definitions, and practical examples. The framework's three components—“Basis” (philosophy and principles), “Wh...

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.064
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.064
Threshold uncertainty score0.337

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0640.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.009
Scholarly communication0.0070.004
Open science0.0020.012
Research integrity0.0020.003
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 head0.291
GPT teacher head0.388
Teacher spread0.096 · 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 source (direct Gemma or distilled Codex), 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

Citations63
Published2015
Admission routes1
Has abstractyes

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