Implications of the Increasing Convergence of Video Gaming and Gambling: A Narrative Review
Bibliographic record
Abstract
ABSTRACT Two of the most popular recreational activities, video gaming and gambling, have converged in a number of different ways including through (1) social casino gaming, (2) loot boxes, (3) skin betting, (4) esports betting, and (5) play-to-earn video gaming. These convergences have brought about concerns, surrounding the increased risk of problems related to excessive use. The present paper reviews the current literature across these 5 areas of convergence, summarizing the implications for policy and future research. The findings from our review generally underscore the modest to strong increase in risk for harms due to these convergences that has important policy implications for regulation. However, much of the research continues to draw from convenience sampling and cross-sectional study designs. Therefore, though concerns regarding continued convergence persist, there is a strong need for further research in this area that utilizes more rigorous methods and employs a broader assessment of both video gaming and gambling engagement. Deux des activités récréatives les plus populaires, les jeux vidéo et les jeux d’argent, ont convergé de différentes manières, notamment par le biais : (1) des jeux de casino sociaux, (2) des coffres de butin, (3) des paris Skin, (4) des paris sportifs en ligne, et (5) des jeux vidéo où l’on gagne de l’argent. Ces convergences ont suscité des inquiétudes quant au risque accru de problèmes liés à une utilisation excessive. Le présent document passe en revue la littérature actuelle dans ces cinq domaines de convergence, en résumant les implications pour la politique et la recherche future. Les résultats de notre examen soulignent généralement l’augmentation modeste à forte du risque de dommages due à ces convergences, qui a d’importantes implications politiques pour la réglementation. Toutefois, une grande partie de la recherche continue de s’appuyer sur des échantillonnages de commodité et des études transversales. Par conséquent, bien que les inquiétudes concernant la poursuite de la convergence persistent, il est absolument nécessaire de poursuivre les recherches dans ce domaine en utilisant des méthodes plus rigoureuses et en procédant à une évaluation plus large des jeux vidéo et de l’engagement dans les jeux d’argent.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".