The Illusion of Control in Online Slot Machine Gambling: A Conceptual Extension of Langer and Roth (1975)
Bibliographic record
Abstract
This study investigates how different patterns of win/loss outcomes in an online slot machine task influence participants' perceptions of control. In the original study by Langer and Roth (1975), participants predicted the outcomes of 30 coin tosses, receiving immediate feedback on whether each prediction was correct. Participants were assigned to three different sequences of win/loss outcomes: descending (i.e. a cluster of early wins), ascending (a cluster of late wins), or flat (equally distributed wins). The outcome sequences influenced subsequent perceptions of control, such that individuals presented with early wins overestimated their ability on the task. The Langer & Roth finding was recently confirmed in an online conceptual replication by Eben et al (2022), but the coin toss task has limited ecological validity to real-world gambling. The current project adapts the original sequence conditions to an online slot machine task, where participants will experience one of the three outcome patterns over 30 trials. The win-loss ratio is identical across conditions, but the conditions differ in the temporal pattern of winning. After the task, participants will answer questions adapted from Langer and Roth (1975) to assess the illusion of control. We will also assess behavioural variables (bet size and initiation speed) to further understand the effect of outcome sequences in slot machines.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".