Use of Netnography to Understand GoFundMe® Crowdfunding Profiles Posted for Individuals and Families of Children with Osteogenesis Imperfecta
Bibliographic record
Abstract
Osteogenesis imperfecta (OI) is a rare genetic disorder associated with low bone density and increased bone fragility. OI can lead to a variety of supportive and medical care needs; yet financial impacts for families and individuals living with OI remain understudied and largely invisible. Efforts by families to recover costs through GoFundMe®, the most important crowdfunding web platform worldwide, offer an unprecedented opportunity to gain insight into OI costs. The purpose of this study was to describe GoFundMe® profiles and determine what factors may contribute to funding goal achievement. A netnographic approach was used to investigate a publicly available dataset from GoFundMe®, with 1206 webpages extracted and 401 included for analysis. Most webpages originated from the United States and were created by family members. Nineteen cost categories were identified. Thirty-seven web profiles met their funding goal. Funding increases or goal achievements created for children were associated with increased social-media exposure (i.e., Facebook). This study helped to describe and showcase the financial impacts of OI and effectiveness of a crowdfunding website to alleviate costs. The results highlight the need for further research to better understand OI costs and provide economic supports for individuals with OI.
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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 | 0.000 | 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 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".