Contextual Typologies: Gambling Practices among University Students
Bibliographic record
Abstract
In recent decades, research on gambling has largely focused on the description of gambling behaviours and problems, and on the psychological determinants of excessive behaviours (Aasved, 2003b). It is our contention that these conceptual orientations have ignored the role of the proximal social context as a significant determinant of gambling patterns and problems. In response to this limitation, we suggest conceptualizing gambling behaviours as social practices that are expressed and empirically observed in proximal contexts through a triad of dimensions including the type of activity, the relationship to gambling partners and the location. Given the scarcity of research on the social context of gambling, however, this contextual study of gambling is exploratory in nature. It aims primarily at identifying groups of gambling practices among university students and examining the association between the identified groups and related problems. These problems namely include gambling problems, alcohol and illicit drug use and psychological distress. The sample (N=861) was drawn from the University Student Gambling Habit Survey 2008 (ENHJEU), conducted among a representative sample of undergraduate students in three universities and three affiliated schools in Montreal, Canada. A multiple correspondence analysis was performed to generate groups of gambling patterns based on the combination of three characteristics of the gambling context including the activity, the gambling locations and the partners. The analysis revealed three groupings of activities and eight distinct groups of contexts. Three groups were found to be associated with problem gambling while none of the other risk-behaviours had any association. The discussion brings about the role of contexts in shaping gambling as collective social practices and the association between specific constellations of contextual factors and gambling problems. It concludes with a broader reflection on new approaches to comprehend gambling in the context of modernity.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".