Publicidad de apuestas y conducta de juego en adolescentes y adultos jóvenes españoles
Bibliographic record
Abstract
The profits obtained by the gambling industry in Spain represent almost one point of GDP and the proportion of minors who have gambled has reached a quarter. This situation occurs despite the law regulating gambling, which included among its objectives the prevention of addictive behaviors, as well as the protection of minors and other vulnerable groups. Recently, an additional regulation was approved to control gambling advertising. Bearing in mind the new regulatory context, we analyze the relationship between advertising and gambling in adolescents and young adults, studying especially young people who have already gambled and minors. We conducted an empirical investigation with a sample of 2,181 adolescents and young adults who filled out a questionnaire on gambling and advertising. We found that the variables associated with advertising are significantly related to gambling behavior and that, in addition, this correlation occurs with greater magnitude in men. We obtained higher scores in advertising influence among those subjects who have ever gambled compared to those who have not, highlighting the importance of discouraging the arrival of new gamblers. Regarding minors, we found significant differences in the different variables of advertising influence compared to young adults. These findings point to the need to evaluate this influence considering the new habits and interests of minors today.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".