Parables of care: Instrumentality, aesthetics and utility in devising a comic for dementia caregivers
Bibliographic record
Abstract
Conference presentation delivered at the Comics & Medicine Conference (June 2017), in Seattle, Washington. \n\n This presentation reports on work in progress by Ernesto Priego at City University of London, Peter Wilkins at Douglas College, and Simon Grennan at The University of Chester to develop two short comic book manuals of best practices for dementia care in the UK and Canada. This project collects information in focus groups from caregivers from across disciplines (e.g. nurses, psychiatric nurses, healthcare support workers, therapeutic recreation practitioners, dental assistants) in consultation with comic book artists to create comics that speaks to a variety of audiences. The project explores the possibility of synthesizing qualitative data--interdisciplinary attitudes and approaches--in comics form. So doing it tackles a logistical problem (gathering the information) and a technical one (representing the information). Furthermore, the project looks at the significance of the aesthetics of conveying information: what are the advantages of depicting best practices in comic book form as opposed to using an infographic or other document. Do caregivers (and family members of dementia sufferers) find the information in comics form more subjectively and objectively accessible than in other conveyances. We are intrigued by the possibility that the artistic representation of medical information develops and enhances empathy and identification that otherwise might be suppressed. The project also explores the different practices and approaches of two different health systems: the NHS in the UK and health authorities in British Columbia, Canada. The differences between the two comics will illuminate discrepancies between the two systems vis a vis dementia care and provide opportunities to analyze those discrepancies. At the time of the conference, we will be in the middle of the project, and we propose to present how it is going, the pitfalls and triumphs. We will be able to report on the focus groups/ artist consultations and show some preliminary work on the comics.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".