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Record W2598028271

Exercise modality and its relationship with global self-esteem and physical self-concept

2016· article· en· W2598028271 on OpenAlexaff
Jasmine Proulx, Lori Dithurbide

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsDalhousie University
Fundersnot available
KeywordsModality (human–computer interaction)ModalitiesPreferencePsychologySelf-esteemAerobic exerciseClinical psychologyPhysical therapyMedicineGerontologyComputer scienceMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

Research in the field of physical activity and self-esteem has been conducted since the 1970's. However, there have been very few studies examining the strength of the relationships between exercise modality (aerobic, group/classes, light, and heavy resistance), global self-esteem (GSE), and physical self-concept (PSC) in young, healthy women. The purpose of this study was to determine the strength of the relationship between GSE and PSC depending on a) the most frequently performed and b) the most preferred exercise modality. The secondary objective was to examine how PSC and its subdomains differ between exercise modalities. Women who exercise regularly and are between the ages of 18-30 were invited to participate in the study. Data was collected electronically through the online survey software Opinio. The online questionnaire consisted of 5 measures: tables for exercise habits, the Rosenberg Self-Esteem Scale, and 3 measures of PSC. For analysis, the data was divided into heavy resistance training (HRT) and others based on frequency and preference. There were no significant differences in the strength of the relationships between PSC and GSE in either group. Women who perform HRT most frequently and/or prefer HRT to other modalities had greater PSC while only women that perform HRT most frequently had greater GSE. While it is unknown at this time if HRT has a direct effect on GSE and PSC, more research should be conducted to further examine these and other potential relationships and effects.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.286
Teacher spread0.267 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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