Student Gambling: Involvement and Prevalence of Problem Gambling among Sports Bettors of the University of Cape Coast, Ghana
Bibliographic record
Abstract
Problem gambling refers to the adverse effects on the gambler, on other individuals, his/her social life or even on the community as a result of the individual’s excessive gambling behaviour. Hence, the purpose of this study was to investigate the involvement, prevalence and counselling implication of problem gambling among student sports bettors of the University of Cape Coast. The study explored the various sub-types of gambling that students are involved in and are prevalent in the University. The Pathways Model of Blaszczynski and Nower was used in identifying subtypes of problem gamblers. A descriptive survey design was adopted for the study. A sample size of 351 was used from four colleges of the University of Cape Coast. The researchers further used disproportionate stratified sampling technique to draw from each college the number required for the study. The Canadian Problem Gambling Index on a whole recorded Cronbach alpha value of .81. Means, standard deviation and percentages were used in the data analysis. It was found that non-problem gamblers and problem gamblers were most prevalent among the sub-types. Also, students were found to involve in gambling mostly twice or more in a week. On timely basis, 25mins or more were spent on sports betting. It was recommended among other things that a proposed ‘Gaming Research Unit’ under the auspices of the Department of Education and Psychology, should be set up to ensure the screening of students who are low-risk, moderate-risk or problem gambler and referred them for guidance and counselling and also organise gambling educational programmes and awareness seminars in the University of Cape Coast. Keywords: Problem Gambling, Sports bettors, Prevalence, Student gambling, Involvement DOI: 10.7176/JEP/14-5-01 Publication date: February 28 th 2023
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".