Anthony and the Role of Silence in Portraiture in Clinical Settings
Bibliographic record
Abstract
This article describes one collaborative arts-based research project.Portrait artist Mark Gilbert and coinvestigators consider lessons for art and healing from one patient, Anthony, whose experience of head and neck cancer diagnosis, surgery, and recovery suggests how silence is ethically, artistically, and clinically significant.Portraits of Care At the request of Virginia Aita and the fourth author (WL), the first author (MG) was invited to coconduct an arts-based research study using portraiture to investigate care and caregiving.In this mixed-methods study, MG drew and painted patients and their caregivers.The project culminated in an exhibit, Here I Am and Nowhere Else: Portraits of Care (POC) and was displayed at the Bemis Center for Contemporary Arts in 2008-2009.1 This exhibit featured visual art as a means of cultivating deeper understanding of ethical and aesthetic values expressed in the experiences of patients, family caregivers, clinicians, and others-janitors, biomedical researchers, public health professionals, and policymakers, for example-working in health care.POC considered portraiture to be an untapped resource in health care that could be used to "imagine the humane dimensions, cultural frameworks and processes that shape human experiences of health and illness." 2 The relationship that MG shared with one POC participant, Anthony, is especially illustrative of this purpose.Although this essay about Anthony is conveyed in MG's voice, this work has been a collaboration among the 4 authors.Anthony I first met Anthony in the company of WL just prior to his tumor resection surgery.Anthony had graying hair tied back in a ponytail.His thin beard covered, but could not hide, a protruding cancer that enveloped most of his mandible, lower jaw, and tongue.When Anthony first noticed the tumor, he avoided treatment and traveled around the Midwest by himself.MG wondered why Anthony delayed seeking treatment and if his finally doing so was at the behest of his sister Gloria, who accompanied him that day to the clinic.Anthony was soft spoken, and his voice was somewhat muffled, as the tumor restricted movement of his tongue and jaw.His surgery that day would leave him unable to communicate verbally and therefore would illuminate the ethical and aesthetic roles of silence in MG's subsequent interactions with him.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.051 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".