This time with feeling: In-play sports betting as a vehicle for emotion regulation.
Bibliographic record
Abstract
OBJECTIVE: The purpose of this research was to assess factors (i.e., emotion regulation, impulsivity) that motivate in-play sports betting. Specifically, we examined whether individuals report increased excitement after placing an in-play bet and whether trait negative and positive urgency moderate the effect of emotion regulation motives on in-play betting frequency. METHOD: = 239) residents who reported placing at least one in-play bet during the respective sporting events. Participants completed self-report measures of excitement, emotion regulation motives, in-play betting frequency, problem gambling, and trait affective impulsivity. Data from the three studies were pooled to conduct an integrative data analysis (IDA). RESULTS: < .001) to predict in-play betting frequency, such that the bivariate effects were amplified among those higher (relative to lower) in trait affective impulsivity. CONCLUSIONS: In-play sports betting is an exciting activity that people who gamble may engage in to regulate their emotions. These effects are amplified in those with high trait affective impulsivity. Responsible gambling tools such as mandatory play breaks may discourage the continuation of impulsive betting episodes. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".