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Record W2124746100 · doi:10.1177/1524839907307886

Process Evaluation of a School-Based Intervention to Increase Physical Activity and Reduce Bullying

2008· article· en· W2124746100 on OpenAlexaff
Donna Bowes, Monica Marquis, Wendy B. Young, Philippa Holowaty, Winston Isaac

Bibliographic record

VenueHealth Promotion Practice · 2008
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsToronto Metropolitan UniversityHalTech
Fundersnot available
KeywordsIntervention (counseling)Process (computing)Physical activityPsychologyApplied psychologyMedical educationEnvironmental healthMedicineComputer sciencePhysical therapyPsychiatry

Abstract

fetched live from OpenAlex

Increases in schoolyard bullying and physical inactivity have become important issues to many stakeholders. Peers Running Organized Play Stations (PROPS) is a program designed to address these two issues in elementary schools. Using a "train the trainer" approach, PROPS was introduced to 41 schools. Results of a process evaluation indicate that the implementation rate was 39%. Resources were identified by some respondents as an implementation facilitator. A variety of barriers to implementation were identified: The PROPS program was not a component of anyone's job at the school level, teachers or parent volunteers are needed to run the program, and there is no funding to purchase equipment or storage bins for the equipment. In addition, support for PROPS is vulnerable to changing environments. This process evaluation points to some needed changes for long-term sustainability of the program while highlighting challenges associated with implementing a program in the elementary school setting.

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)0.017
metaresearch head score (Gemma)0.022
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.531
GPT teacher head0.555
Teacher spread0.024 · 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

Citations24
Published2008
Admission routes1
Has abstractyes

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