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Record W2905850025 · doi:10.32920/ryerson.14643672

"There's No Boys' and Girls' [Sports], They Share" : Young Girls' Experiences With Team Sports

2021· preprint· en· W2905850025 on OpenAlexaff
Heather Judith Christian

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsToronto Metropolitan UniversityEducation and Early Childhood Development
Fundersnot available
KeywordsPsychologyTeam sportYouth sportsSport managementMedical educationApplied psychologyPublic relationsAthletesMedicinePhysical therapyPolitical science

Abstract

fetched live from OpenAlex

Research has identified many benefits of participating in team sports. These examinations have discovered that girls are less likely to participate in team sports than boys. This study examines the reasons why girls do or do not participate in team sports. In this qualitative study, girls aged 6 to 9 were interviewed about their experiences that have either led them to participate in team sports or not participate in team sports. Through this study it was discovered that the family and peer group play a major role in influencing team sports participation in young girls. I found that the interviewed girls believe that boys are more successful in team sports, that sports skills are gendered and there are many ways to improve team sports participation for other young girls. Through the identification of factors which encourage or discourage participation in team sports, practitioners will be better informed on how they may support girls in participating in team sports.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0060.004
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.278
Teacher spread0.261 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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