A Study on the Irrational Gambling Beliefs and Superstitions Among Young Problematic Cryptocurrency Investors
Bibliographic record
Abstract
This study aims to explore the irrational gambling beliefs and superstitions held by young problematic virtual asset investors. To achieve this objective, we selected a total of eight participants classified as ‘high risk group’ according to the K-MAGS (Korean Gambling Addiction Screening Tool) and the CPGI (Canadian Problem Gambling Index) and conducted one-on-one in-depth interviews. The phenomenological research method developed by Giorgi (1970; 1985) was employed to understand the essence of the phenomenon. Five themes related to irrational gambling beliefs were identified: technology-oriented attitudes, beliefs in self-control, confidence in returns, unrealistic optimism, and the belief that relationship-oriented investments will lead to success. Additionally, three themes regarding superstitions were identified: time-related superstitions, location-related superstitions, and superstitions related to personal behavior. Based on these findings, a general structural description was provided, and implications for addressing cognitive errors, such as irrational gambling beliefs and superstitions, were suggested.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".