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Record W2095416247 · doi:10.1080/08964289.2011.571305

Does Race or Sex Moderate the Perceived Built Environment/Physical Activity Relationship in College Students?

2011· article· en· W2095416247 on OpenAlexaff
Kathryn Lightfoot, Chris M. Blanchard

Bibliographic record

VenueBehavioral Medicine · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologyRace (biology)Physical activityBuilt environmentNeighbourhood (mathematics)GerontologySocial psychologyDemographyClinical psychologyMedicinePhysical therapy

Abstract

fetched live from OpenAlex

The purpose of this research was to explore the relationship between the perceived built environment and physical activity (PA) among college students, and to determine whether race and/or sex moderate this relationship. Participants were 785 college students (435 students in Study 1 and 350 in Study 2). Students completed questionnaires assessing characteristics of their neighborhood, and were followed up 1 (Study 1) or 2 (Study 2) weeks later to measure PA levels. Seeing others in one's neighbourhood being active was found to be significantly related (p<.01) to higher levels of PA for students in both studies. In Study 2, race was found to moderate the relationship between having many places within walking distance and PA, affecting African Americans more strongly than Caucasians. Sex was not found to moderate the perceived built environment/PA relationship. It appears that certain aspects of the perceived built environment may have an effect on the level of PA in college students, with race moderating this relationship.

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)0.003
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 score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.136
GPT teacher head0.396
Teacher spread0.260 · 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

Citations13
Published2011
Admission routes1
Has abstractyes

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