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Record W4296131782 · doi:10.1177/15588661221125469

A Review of Campus Recreation and Sport-Based Experience Literature in Higher Education Contexts

2022· review· en· W4296131782 on OpenAlexaff
Kevin Wilson

Bibliographic record

VenueRecreational Sports Journal · 2022
Typereview
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsScopusRecreationData extractionCitizen journalismWeb of scienceEmpirical researchSociologyPsychologyApplied psychologyMedical educationWorld Wide WebComputer sciencePolitical scienceMEDLINEMedicineEpistemology

Abstract

fetched live from OpenAlex

This rapid review was conducted to synthesize the empirical research related to campus recreation participatory experiences that was published between 2011 and 2021. To carry out the review, three databases (SPORTDiscus, Web of Science, Scopus) were systematically searched for peer reviewed empirical literature related to campus recreation participatory sport experiences. The results were then screened with predetermined criteria and 180 studies remained for data extraction. Data was extracted and trends were identified for discussion. When comparing the results to a similar review conducted on literature published between 1998–2010 (cf. Barcelona & Sweeney, 2012), the results of the reveal that the use of theory is becoming increasingly prevalent as scholars are more regularly providing theoretical frameworks, key constructs and discussing scholarly contributions. The review also revealed limitations such as inconsistencies with measurement and that most studies have been conducted at single institutions, which should both be addressed in future research.

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)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0160.018
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.054
GPT teacher head0.390
Teacher spread0.336 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations8
Published2022
Admission routes1
Has abstractyes

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