Social Responsibility Tools in Online Gambling: A Survey of Attitudes and Behavior among Internet Gamblers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To date, little empirical research has focused on social responsibility in gambling. This study examined players' attitudes and behavior toward using the social responsibility tool PlayScan designed by the Swedish gaming company Svenska Spel. Via PlayScan, players have the option to utilize various social responsibility control tools (e.g., personal gaming budgets, self-diagnostic tests of gambling habits, self-exclusion options). A total of 2,348 participants took part in an online questionnaire study. Participants were clientele of the Svenska Spel online gambling Web site. Results showed that just over a quarter of players (26%) had used PlayScan. The vast majority of those who had activated PlayScan (almost 9 in 10 users) said that PlayScan was easy to use. Over half of PlayScan users (52%) said it was useful; 19% said it was not. Many features were seen as useful by online gamblers, including limit setting (70%), viewing their gambling profile (49%), self-exclusion facilities (42%), self-diagnostic problem gambling tests (46%), information and support for gambling issues (40%), and gambling profile predictions (36%). In terms of actual (as opposed to theoretical) use, over half of PlayScan users (56%) had set spending limits, 40% had taken a self-diagnostic problem gambling test, and 17% had used a self-exclusion feature.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it