Examining Antecedents and Consequences of Gambling Passion: The Case of Gambling on Horse Races
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
OBJECTIVE: This study investigated the antecedents and consequences of gambling passion using structural equation modeling to examine relationships among gambling motivation, passion, emotion, and behavioral intentions in the horse racing industry. METHODS: An onsite survey was conducted with 447 patrons at a horseracing park in South Korea. A confirmatory factor analysis showed that the Gambling Passion Scale was valid and reliable, resulting in two sub-scales: obsessive passion (OP) and harmonious passion (HP). RESULTS: Study results indicated that extrinsic motivation influenced OP whereas intrinsic motivation significantly affected HP. Furthermore, OP was correlated with negative emotion, whereas HP was related to positive emotion. Gamblers' satisfaction was found to be influenced positively by positive emotion and negatively by negative emotion. Finally, satisfaction appeared to affect gamblers' behavioral intentions. CONCLUSION: Study results echoed the notion of distinct and separate gambling motivations and passions among horse racing gamblers. Furthermore, results identified specific areas to which horse racing operators or policy makers should pay special attention in developing effective marketing strategies to promote responsible gambling.
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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