Slot machine gambling and testosterone: Evidence for a “winner–loser” effect?
Bibliographic record
Abstract
= 113) were recruited into a quasi-experimental design involving 15 min of authentic slot machine gambling, incentivized by a $10 cash bonus for participants who finished in profit. In addition to salivary measures of testosterone, salivary cortisol and self-reported anthropomorphization of the slot machine were tested as potential moderators. Contrary to predictions, winning and losing slot machine sessions did not exert significant differential effects on testosterone, and this pattern was not moderated by cortisol levels or slot machine anthropomorphization. Exploratory analyses tested relationships between subjective gambling experiences in the sessions and testosterone change. Higher positive affect and flow predicted greater testosterone declines from pre- to postgambling. The testosterone results add to a growing literature on the boundary conditions of the winner-loser effect and inform future studies on testosterone reactivity in relation to gambling and disordered gambling. The tendency to anthropomorphize slot machines is a neglected cognitive distortion in gambling that merits further study. (PsycINFO Database Record (c) 2018 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".