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Record W2186684891 · doi:10.36510/learnland.v1i1.238

Examining Ways in Which Youth Conferences Can Spell Out Gains in Community Youth Development and Engagement

2007· article· en· W2186684891 on OpenAlexvenueno aff
Felicia Sanders, Marcela A. Movit, Dana L. Mitra, D. F. Perkins

Bibliographic record

VenueLEARNing Landscapes · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsPositive Youth DevelopmentSpellAgency (philosophy)Sense of agencyCompetence (human resources)Public relationsDiversity (politics)PsychologyDemocracyPolitical sciencePedagogySociologySocial psychologyDevelopmental psychologyPoliticsSocial science

Abstract

fetched live from OpenAlex

With student outcomes increasingly becoming associated witht est scores, schools are less able to dedicate themselves to helping students learn how to become engaged and active participants in a democracy. As a result, other community based organizations have stepped in to help students acquire the sense of agency, belonging, and competence—known as the "A, B, C’s" of youth development—that research has shown to be crucial for youth to become contributing citizens. Drawing on survey, interview and observational data, this paper considers how two such organizations give students an opportunity for personal development, while providing youth with leadership skills and opportunities to engage in their schools and communities. This research suggests that in addition to the traditional "A, B, C’s," it may be beneficial to consider aspects of diversity—proposed here as "D"—that play an important role in youth development, as well as the synergy of all four components of youth development that result in positive student outcomes.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.342
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.143
GPT teacher head0.317
Teacher spread0.174 · 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 designObservational
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

Citations5
Published2007
Admission routes1
Has abstractyes

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