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Record W2160297018 · doi:10.1123/jsep.27.3.311

The Effect of Exercise on Global Self-Esteem: A Quantitative Review

2005· review· en· W2160297018 on OpenAlexaff
John C. Spence, Kerry R. McGannon, Pauline Poon

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2005
Typereview
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyMatching (statistics)Self-esteemPhysical fitnessApplied psychologySelection (genetic algorithm)Social psychologyPhysical therapyGerontologyClinical psychologyStatisticsMedicineComputer scienceArtificial intelligenceMathematics

Abstract

fetched live from OpenAlex

The purpose of this study was to quantitatively review the body of research on exercise and global self-esteem (GSE). This review focuses specifically on studies using adults and also incorporates both published and unpublished works. Computer and manual searches identified 113 studies matching the selection criteria. Each study was coded according to 20 study features. A total of 128 effect sizes (d) were derived. As indicated by effect-size magnitude, participation in exercise brought about a small change in GSE (d = +0.23). Change in physical fitness and type of program were significant moderators of the effect of exercise on GSE. Larger effect sizes were observed for those who experienced significant changes in physical fitness and those participating in exercise or lifestyle programs as opposed to skills training.

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)0.018
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.041
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0120.012
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.041
GPT teacher head0.433
Teacher spread0.391 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations221
Published2005
Admission routes1
Has abstractyes

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