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Associations between participation in a Physical Activity‐Based Positive Youth Development Program and Academic Outcomes

2019· article· en· W2984025773 on OpenAlexaff
Lindley McDavid, Meghan H. McDonough, Janet B. Wong, Frank Snyder, Yumary Ruiz, Bonnie B. Blankenship

Bibliographic record

VenueJournal of Adolescence · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPositive Youth DevelopmentPsychologyOddsTest (biology)Propensity score matchingNature versus nurtureAcademic achievementDevelopmental psychologyDisadvantagedEthnically diverseHead startDemographyLogistic regressionPopulationMedicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Physical activity-based positive youth development (PYD) programs offer asset building experiences to foster the overall well-being of youth. These programs have the potential to enhance success in other important contexts for children, such as school. However, rigorous examination of this potential impact is needed. METHODS: Propensity score matching was used to compare school outcomes among children who participated in a short, summer physical activity-based PYD program in the USA and children who were from similar backgrounds and from the same school district but did not attend the program. The sample included 149 pairs of students aged 7-12 years (M = 10.11, SD = 1.26) and, in each group, 62% were from ethnically diverse backgrounds, 38% were from primarily Caucasian backgrounds, and 80 were female and 69 were male, and birth years were equally distributed. Ordinal and logistic regression models were used to test for differences between standardized math and language arts test scores, excused and unexcused absences, and total suspensions and expulsions between the two groups. RESULTS: (1, N = 298) = 5.58, p = .02) respectively. No other significant differences were found. When using a more rigorous quasi-experimental and longitudinal design, participation in a PYD program predicted some but not all academic performance and behaviors. PYD programs may need to be designed to specifically nurture academic skills to consistently impact academic 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)0.001
metaresearch head score (Gemma)0.000
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 score0.052
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.060
GPT teacher head0.394
Teacher spread0.334 · 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

Citations12
Published2019
Admission routes1
Has abstractyes

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