Crowdfunding Cannabidiol (CBD) for Cancer: Hype and Misinformation on GoFundMe
Bibliographic record
Abstract
Objectives. To use crowdfunding campaigns to better understand how cannabidiol (CBD) is represented (and misrepresented) as cancer-related care. Methods. We analyzed CBD-related crowdfunding campaigns (n = 155) created between January 2017 and May 2019 in multiple countries on GoFundme.com . Results. More than 81.9% of campaigns fundraised CBD for curative or life-prolonging reasons, and 25.2% fundraised for pain management. Conclusions. Most campaigns seeking funds for CBD for cancer-related care on GoFundMe are for curative or life-prolonging purposes and present CBD definitively as an effective treatment option. In general, campaigners supported their funding requests with anecdotal claims of efficacy and referenced sources of information that were either not evidence-based or that misrepresented existing evidence. Public Health Implications. Misinformation around CBD for cancer is widespread on medical crowdfunding campaigns. Given the potential adverse impact, crowdfunding platforms, like GoFundMe, must take steps to address their role in enabling and spreading this misinformation.
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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 | 0.011 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".