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Record W3213367563 · doi:10.1080/07448481.2021.1967364

Exercise behaviors and resource use among graduate students at a Canadian university: A cross-sectional study

2021· article· en· W3213367563 on OpenAlexaffabout
Joyla A. Furlano, Anisa Morava, Michelle Y. Wong, Wuyou Sui, Joseph Munn, Harry Prapavessis

Bibliographic record

VenueJournal of American College Health · 2021
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsWestern University
Fundersnot available
KeywordsCross-sectional studyMedical educationGraduate studentsResource (disambiguation)PsychologyCollege healthPhysical activityMedicineGerontologyPhysical therapyFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Participation in regular exercise among post-secondary students is often low. Our cross-sectional study aimed to assess exercise levels, perceived barriers/motivators to exercise, and knowledge and use of exercise resources in graduate students. PARTICIPANTS: We recruited graduate students across various disciplines at a large Canadian university. METHODS: = 540) completed an anonymous mixed methods online survey. RESULTS: Approximately 11% of participants reported not participating in any form of weekly exercise, and only 9.4% met the Canadian Physical Activity Guidelines. The most common barrier and motivator to exercise was time commitment and improving physical health, respectively. Some participants were aware of available exercise services but most did not use them. Suggestions for improving services included having graduate-dedicated exercise space and resources. CONCLUSIONS: Low exercise participation among graduate students may be due to a lack of education of available resources or a lack of existing resources that meet their specific needs.

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)0.000
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 score0.044
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.355
Teacher spread0.300 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

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