What was lost, missing, sought and hoped for: Qualitatively exploring medical crowdfunding campaign narratives for Lyme disease
Bibliographic record
Abstract
Lyme disease remains a contested illness in Canada, thereby making the diagnostic and treatment journeys difficult for some people. One outcome of this is that increasing numbers of people are turning to medical crowdfunding to support access to alternative therapies, non-local health care providers and assist with managing the costs of everyday life. In this analysis, we qualitatively explore the narratives shared in Canadians' crowdfunding campaigns to support Lyme disease treatment or diagnosis to identify whether or not any common elements shared in these narratives exist, and if so, what they are. We identified 238 campaigns for inclusion from three prominent crowdfunding platforms. Thematic analysis of the campaign narratives shows four consistent themes shared in these campaigns: what is lost (e.g. bodily ability), what is missing (e.g. local care options), what is sought (e.g. funds to cover treatment abroad) and what is hoped for (e.g. return to wellbeing). These themes demonstrate the highly personal and emotional nature of medical crowdfunding, particularly in the context of a contested illness that may lead some to question the legitimacy of one's financial need. This analysis contributes valuable new insights to the nascent scholarship on medical crowdfunding, and particularly to our understanding of how people communicate about their health and bodily needs on this public platform. It also identifies important directions for future research, including the potential for crowdfunding narratives to be used for advocacy.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.018 | 0.020 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".