Does the unavailability of social media affect online gambling behavior? A behavioral tracking data study before and after the October 2021 Facebook outage
Bibliographic record
Abstract
Background and aims: on October 4, 2021 created a unique possibility to investigate this relationship. The present study examined whether patterns of online gambling were different during the time of the social media outage from what could be expected during that time based on historical behavioral tracking data. Methods: that included information on the gambling behavior of 232,037 individuals from Croatia, Czechia, Poland, Romania, and Slovakia on five consecutive Mondays, including the day of the social media outage, on two different types of gambling activity: gaming (such as online casino games) and sports betting. A linear regression was estimated for several outcome variables (number of people gambling, amount of stake, number of bets) separately for each country and gambling type, while gender, age, time, and date were included as control variables. Results: outage only had a marginal impact on gambling behavior. Discussion and Conclusions: Further research and analysis are needed to explore the relationship between social media use and online gambling behavior.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".