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Record W4410466144 · doi:10.1080/14927713.2025.2503183

Parental involvement in youth sports: historical trends and links to generational, socioeconomic status, sport culture, and youth sport commitment contexts

2025· article· en· W4410466144 on OpenAlexvenueno aff
Chris Knoester, Chris Bjork

Bibliographic record

VenueLeisure/Loisir · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusYouth sportsSociology of sportYouth culturePsychologySport managementSociologySocial psychologyPolitical scienceGender studiesDevelopmental psychologyPublic relationsAthletesDemographyMedicinePopulation

Abstract

fetched live from OpenAlex

Using data from the National Sports and Society Survey (N = 3,993) and multiple regression analyses, this study examined parents’ involvement in their children’s youth sports participation activities. We considered historical trends in parents’ attendance at their children’s sporting events, time spent otherwise supporting their children’s youth sports endeavours, and the amount of money that families allocate to their children’s sports activities. We found generational, socioeconomic status, family and community sport culture, and youth sport commitment associations with parents’ involvement patterns. Parents’ involvement generally increased across generations, became more differentiated by family socioeconomic status, and was largely connected to sport cultures and children’s sports commitments, of course. Patterns were largely similar for parents’ frequencies of attendance at their children’s sporting events, parents’ frequencies of support for their children’s sports participation, and family expenditures on their children’s sports participation.

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)0.002
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.286
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 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

Citations6
Published2025
Admission routes1
Has abstractyes

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