Rationalization as a Dissonance Management Strategy among Electronic Gambling Machine Players
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
Erroneous gambling-related beliefs are well researched in light of their association with problem gambling, with some research suggesting these beliefs also serve as justifications for gambling behaviour. The process of justification (i.e., rationalization) can provide insights into how those who gamble resolve dissonance resulting from persistent loss in the gambling context. Using in-depth interviews of 43 participants who identified electronic gambling machines as their preferred game type and were either experiencing gambling problems or were at risk of developing a problem, this study details how dissonance is managed through rationalizations in line with the Dawson (1999) framework. This framework is based on research of religious groups surviving prophetic disconfirmation and is employed here to highlight the contextual and socio-cultural underpinnings of rationalizations along with their supernatural and pseudo-religious qualities. Rationalizations reflect broader socio-cultural beliefs around morality, work, speculation, perseverance, and the supernatural. Implications for treatment are discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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