Trust in Internet gambling and its association with problem gambling in university students
Bibliographic record
Abstract
The Internet has become a major means of accessing a variety of gambling activities. As a result, there is concern that the Internet may provide more opportunities for consumers to engage in problematic gambling behaviours. The current study examined factors related to Internet gambling and problem gambling in a university student sample (N = 325). Measures included the South Oaks Gambling Screen, the DSM-IV-TR-Based Questionnaire, the Canadian Problem Gambling Index, and a questionnaire examining Internet gambling behaviours and trust. Internet gamblers (n = 53) reported significantly higher levels of trust in Internet gambling sites than non-Internet gamblers (n = 182) and non-gamblers (n = 90). Among Internet gamblers, significant predictors of problem gambling included level of trust in Internet gambling sites, negative effects of this activity on academic achievement and class attendance, and alcohol consumption while gambling on the Internet. Implications of these findings are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".