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Record W4405470836 · doi:10.37333/001c.127558

From personal development to social change: Investigating the long-term impact of an adapted physical activity service-learning program

2024· article· en· W4405470836 on OpenAlexaff
Nikki Matthews, Mary Sweatman, Roxanne Seaman, Emily Bremer

Bibliographic record

VenueInternational Journal of Research on Service-Learning and Community Engagement · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsAcadia University
Fundersnot available
KeywordsTerm (time)Service-learningService (business)Social changePsychologyComputer scienceProcess managementBusinessMarketingPedagogyEconomic growthEconomics

Abstract

fetched live from OpenAlex

Service-learning initiatives provide an experiential learning environment shown to foster academic attitudes, social skills, and future career aspirations. Service-learning also has been effective within adapted physical activity; however, given the lack of research, the magnitude and the long-term impact of programming are not adequately understood. The purpose of this study was to investigate the long-term impact of service-learning within an adapted physical activity setting. Using the Acadia University Sensory Motor Instructional Leadership Experience S.M.I.L.E.® program as the subject of a case study, participants were sent an online survey containing questions on demographic information, disability attitudes, and their S.M.I.L.E. experience. Results from this study presented five themes: (a) Relationship Development, (b) Empathy, (c) Attitude, (d) Accountability, and (e) Knowledge & Skill Development. Results demonstrated that service-learning programming within adapted physical activity can foster positive attitudes toward individuals with disabilities, promoting future civic responsibility, and continuing its influence postgraduation.

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)0.014
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.418
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.008
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 head0.304
GPT teacher head0.512
Teacher spread0.208 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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