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Record W3128558282 · doi:10.3390/su13041744

Exploring the Impact of the COVID-19 Pandemic on Youth Sport and Physical Activity Participation Trends

2021· article· en· W3128558282 on OpenAlexaff
Georgia Teare, Marijke Taks

Bibliographic record

VenueSustainability · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPandemicPhysical activityCoronavirus disease 2019 (COVID-19)Public relationsSport managementSports marketingValue (mathematics)MarketingResource (disambiguation)PsychologySociologyBusinessPolitical scienceMedicineMarketing managementRelationship marketing

Abstract

fetched live from OpenAlex

The COVID-19 pandemic offers youth sport organizations the opportunity to anticipate consumer behaviour trends and proactively improve their program offerings for more satisfying experiences for consumers post-pandemic. This conceptual paper explores potential impacts of the COVID-19 pandemic on changing youth sport and physical activity preferences and trends to inform sport and physical activity providers. Drawing from social ecology theory, assumptions for future trends for youth sport and physical activity are presented. Three trends for youth sport and physical activity as a result of the COVID-19 pandemic are predicted: (1) youths’ preferences from organized to non-organized contexts become amplified; (2) reasons for participating in sport or any physical activity shift for youth as well as parents/guardians; (3) consumers reconceptualize value expectations from youth sport and physical activity organizations. The proposed assumptions need to be tested in future research. It is anticipated that sport organizations can respond to changing trends and preferences by innovating in three areas: (1) programming, (2) marketing, and (3) resource management.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.064
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.202
GPT teacher head0.434
Teacher spread0.233 · 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

Citations40
Published2021
Admission routes1
Has abstractyes

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