Innovations in Research with Medically Fragile Populations: Using Bulletin Board Focus Groups
Bibliographic record
Abstract
A new group of medically fragile young adults are graduating from pediatric palliative care programs with limited expectations to live beyond early adulthood, and no comparable adult services to support their complex needs. Accessing this population is difficult because of the complexity of their conditions, the extensive personal and equipment supports that limit feasibility for travel, and divergent communication abilities. Therefore, we undertook a descriptive case study using an asynchronous modification of an online focus group, a bulletin board focus group (BBFG). The greatest strengths of the BBFG are the appeal of this methodology for young adults and the multi day focus group becomes both a community and an intervention. An important limitation of this method was participant follow through on discussion threads. This BBFG provided rich and varied types of data, and very positive participant experiences.
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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 | 0.121 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".