“The chip in a perfect piece of pottery”: An ethnographic study of parents’ online narratives when a child has cancer
Bibliographic record
Abstract
In recent years, the Internet has increasingly been used to communicate about personal health, illness, and caregiving experiences. For instance, parents of children with cancer share personal accounts online describing their family experiences and emotions as they navigate childhood cancer. These online accounts offer insight into the nature of parents’ experiences and narrative structures adopted to communicate and find meaning. Using a narrative methodology and virtual ethnographic methods grounded in interpretivist and constructivist principles, we examined 23 online accounts of varying lengths shared publicly by Canadian parents of children with cancer. Analysis focused on the content and structure of accounts, identifying common experiences and forms of narration. Three dominant narrative types emerged related to the Idealized Child, Faith, and Failure. To meaningfully convey commonalities across the sample and uphold confidentiality, a Fabrication approach (Markham, 2012) was adopted to develop composites representing the three narrative types, which illuminate family experiences and meaning-making processes. The findings can enhance understanding of family experiences of childhood cancer and inform psychosocial interventions that assist healthcare teams with supporting families of children with cancer more effectively.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".