Financial inducements in gambling marketing: An information disclosure proposal to inform gamblers of their true economic value
Bibliographic record
Abstract
Financial inducements such as free bets are frequently-used gambling marketing offers which temporarily improve a gambler's usual pattern of risk and potential return.Previous research has shown that there are up to 15 distinct types of financial inducements in common use, and that gamblers frequently misunderstand inducements' play-through requirements and other complex terms and conditions.The Australian government has therefore recently banned play-through requirements for inducements shown to new customers, and the Great British regulator the Gambling Commission has recently announced a maximum play-through requirement of 10 times.The present work describes an alternative and yet potentially complementary approach based on disclosing financial inducements' true economic value to gamblers.This approach can be motivated by the fact that financial inducements are not intrinsically harmful, and an understanding of their value has been exploited for profit by some gamblers via techniques called "bonus hunting" and "matched betting".Disclosure-based approaches can be designed to reflect the average losses implied by any play-through requirements, as well as any other terms and conditions which affect their economic value.Disclosure-based approaches for protecting consumers from the potential harms of financial inducements should be subject to further research and policy consideration.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".