Special Supplement: “Creative/Artistic Narratives of Illness”
Bibliographic record
Abstract
Creative expressions of the personal experience of illness have been in the literature for at least three thousand years; the Hebrew Bible, for example, contains the stories of Job, Lazarus, the Centurion’s daughter, and many others who sickened and died. In the Middle Ages and Renaissance, plague and other diseases were rife in Europe, and some of the greatest poetry of Dante, Shakespeare, Jonson, Swift, etc., uses sickness as a central theme. Anne Bradstreet, “the first poet in America,” seems almost obsessed with infant and child mortality in her work - yet it was a common occurrence in daily life of the seventeenth century. In Victorian Canada, the Ontario psychiatrist R. M. Bucke recognized the unique ways literature and medicine could be explored, publishing a book on the well-known poet Walt Whitman. (The relationship of these two men is also the focus of a recent National Film Board production, Beautiful Dreamers - a film which, incidentally, is indebted to the research of CBMH editor Cheryl Krasnick Warsh).
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 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.166 | 0.030 |
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".