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Record W808504817 · doi:10.1123/wspaj.21.1.3

Understanding Physical Activity through the Experiences of Adolescent Girls

2012· article· en· W808504817 on OpenAlexafffundabout
Hope E. Yungblut, Robert J. Schinke, Kerry R. McGannon, Mark Eys

Bibliographic record

VenueWomen in Sport and Physical Activity Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsWilfrid Laurier UniversityLaurentian University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPhysical activityPsychologyDevelopmental psychologyEmic and eticQualitative researchCohortMedicinePhysical therapySociologySocial science

Abstract

fetched live from OpenAlex

Researchers have found that female youths are particularly vulnerable to withdrawing from sport and physical activity programs in early adolescence (see Active Healthy Kids Canada, 2010). However, there is an absence of a comprehensive, emic description of how female adolescents experience physical activity. Open-ended, semi-structured interviews were conducted individually with 15 early adolescent females (12–14 years old) and 20 middle and late adolescent females (15–18years old). Co-participants in the mid to late adolescent cohort provided retrospective accounts of their early adolescent experiences along with insight on how their experiences shaped their current participation. The girls’ voices were brought to the forefront through composite vignettes that highlight their physical activity experiences, integrating the words used by the co-participants. Results are discussed in relation to physical activity programming for adolescent females and why a qualitative approach is useful in contributing to gender-specific physical activity programming.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0050.003
Open science0.0010.005
Research integrity0.0010.003
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 head0.097
GPT teacher head0.343
Teacher spread0.247 · 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

Citations9
Published2012
Admission routes3
Has abstractyes

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