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Record W2133684963 · doi:10.4309/jgi.2014.29.18

Trends in Gambling Behavior among College Student-Athletes: A Comparison of 2004 and 2008 NCAA Survey Data

2014· article· en· W2133684963 on OpenAlexvenueno aff
N. Will Shead, Jeffrey L. Derevensky, Thomas S. Paskus

Bibliographic record

VenueJournal of Gambling Issues · 2014
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAthletesPsychologyDemographyMedicinePhysical therapySociology

Abstract

fetched live from OpenAlex

Two large samples of National Collegiate Athletic Association (NCAA) student-athletes in 2004 (N = 18,916) and 2008 (N = 17,675) were surveyed about their gambling behavior. A cross-comparison highlighted gambling trends among college-student athletes across the four-year span. Overall, past-year and weekly gambling rates were lower in 2008 compared to 2004. There were no within-gender differences in the proportion of individuals at-risk or meeting criteria for a gambling problem between 2004 (4.0% males, 0.3% females) and 2008 (3.8% males, 0.4% females). Participation rates were higher in 2004 for all gambling activities, except for past-year Internet gambling and sports wagering, which increased in 2008 among males. Across sports, gambling participation was notably highest among golfers of both genders. Collectively, the results suggest that gambling activity among student-athletes is on a downward trend in spite of ongoing expansion of gambling opportunities.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.415
GPT teacher head0.517
Teacher spread0.102 · 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.

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

Citations9
Published2014
Admission routes1
Has abstractyes

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