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Record W2143968377 · doi:10.1080/02673843.2015.1067893

The role of youth engagement in positive youth development and social justice youth development for high-risk, marginalised youth

2015· article· en· W2143968377 on OpenAlexaff
Yoshitaka Iwasaki

Bibliographic record

VenueInternational Journal of Adolescence and Youth · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPositive Youth DevelopmentYouth studiesYouth participationYouth engagementAgency (philosophy)Promotion (chess)Economic JusticePublic relationsPsychologyPolitical scienceSociologyDevelopmental psychologyPolitics

Abstract

fetched live from OpenAlex

This article describes reflective experiences documented by our youth leaders and community agency partners (n = 7 & 12, respectively) who have involved in our multi-year community-based research project. Overall, meaningful youth engagement facilitated by youth leadership was highlighted as a key mechanism for positive youth development (PYD) and social justice youth development (SJYD). First, the key PYD-related concepts identified include the following: (1) strengths-based empowering approach to youth engagement, (2) capacity building and positive outcomes for youth and youth-serving agencies and (3) youth-oriented, collaborative research processes that enable the promotion of these positive outcomes (e.g. honouring youth voice: ‘bottom-up process for youth by youth’). Second, the key SJYD-related concepts identified were as follows: (a) activating the voice of youth for social/system change, and (b) advancing research into action – knowledge translation and practical application. The contributions of our youth leaders to youth engagement were shown to be vital to promoting PYD and SJYD.

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)0.007
metaresearch head score (Gemma)0.007
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 score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.008
Scholarly communication0.0060.002
Open science0.0010.014
Research integrity0.0010.002
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 head0.044
GPT teacher head0.299
Teacher spread0.255 · 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

Citations81
Published2015
Admission routes1
Has abstractyes

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