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Record W2964415885 · doi:10.5539/ies.v12n8p83

Empowering High School Students Through Engagement in a Community Event

2019· article· en· W2964415885 on OpenAlexvenueno aff
Steven J. Palazzo, Ella Sanman, Laura E. Bicknell

Bibliographic record

VenueInternational Education Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentHealth promotionSense of communityPsychologyPromotion (chess)Event (particle physics)Medical educationMedicinePublic healthNursingSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Background: Obesity continues to afflict adolescents in underserved communities. It is difficult to understand how adolescents perceive empowerment over their health and the health of their communities. The purpose of our study was to describe the impact of the Healthy Heart Ambassador program on adolescents’ perceived empowerment through the development and implementation of a community event. Methods: High school students designed and implemented a cardiovascular health promotion and disease prevention community event using knowledge acquired through participation in the Teen Take Heart program. The HHA program was created based on the Adolescent Empowerment Model, where participants chose a community event they felt would best deliver the cardiovascular health promotion and disease prevention information. Participants completed a post event survey to evaluate their sense of empowerment while participating in the program. Results: The AES addressed two domains and six attributes of psychological empowerment. The results suggest a sense of empowerment resulted from participating in the student-led community event. Conclusion: During the HHA event students were engaged with other students, teachers, and members of their community who attended the event. In addition, groups of students who did not normally interact with each other were cooperating and working as a team.

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)0.001
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 score0.158
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.094
GPT teacher head0.495
Teacher spread0.402 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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