Does Vice Make Nice? The Viability and Virtuousness of Charity Lotteries
Bibliographic record
Abstract
ABSTRACT Globally, charities are under increasing pressure to find alternative sources of funding. Although charitable gaming has long been considered a viable source of revenue for charities, opponents of gaming have raised concerns about the potential negative consequences associated with gambling. The current paper examines a unique form of charity gaming–the charity super lottery (CSL)–that offers a number of fund-raising benefits to cash-strapped charities. Results from a preliminary study of CSL ticket buyers suggest that the CSL may be both a virtuous and viable source of fundraising. Interviews revealed that CSL consumers (1) viewed the ticket purchase as a donation rather than gambling, (2) were unlikely to be involved in other forms of gambling, and finally (3) perceived the CSL purchase as a complementary rather than supplementary form of charity support behavior. Implications for the fundraisers of charitable organizations and directions for future research are discussed.
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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 | 0.026 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".