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Record W3012848187 · doi:10.1177/1363459320912808

What was lost, missing, sought and hoped for: Qualitatively exploring medical crowdfunding campaign narratives for Lyme disease

2020· article· en· W3012848187 on OpenAlexaffabout
Anika Vassell, Valorie A. Crooks, Jeremy Snyder

Bibliographic record

VenueHealth An Interdisciplinary Journal for the Social Study of Health Illness and Medicine · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinTech, Crowdfunding, Digital Finance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNarrativeContext (archaeology)Public relationsLegitimacyThematic analysisInclusion (mineral)Narrative inquiryHealth careScholarshipPolitical scienceSociologyQualitative researchPsychologySocial psychologyPoliticsSocial science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0090.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.191
GPT teacher head0.445
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2020
Admission routes2
Has abstractyes

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Same venueHealth An Interdisciplinary Journal for the Social Study of Health Illness and MedicineSame topicFinTech, Crowdfunding, Digital FinanceFrench-language works237,207