James Joyce’s Ulysses 100 years later: Flying by the nets of narrative
Bibliographic record
Abstract
n thinking about the theme of this issue of the journal I wanted to explore two great works in literature and what they illustrate about the mind as a healing space.It is exactly 100 years since James Joyce's modernist masterpiece Ulysses[1] was published.I have been reflecting on Ulysses since I finished reading another masterpiece published in the same year, 1922, John Galsworthy's The Forsyte Saga [2].The contrast between the two books is striking and seems to me to epitomize a fundamental tension still being acted out 100 years later: how best to approach suffering both in medicine and in life.The Forsyte Saga tells the story of an upper middle-class family living in London in the late 19 th and early 20 th centuries.The main protagonist is Soames Forsyte who makes a disastrous decision that blights his life and the lives of members of his family over the following 50 years.Soames falls in love with and marries the beautiful Irene who finds that she cannot love Soames.What follows is marital unhappiness, infidelity by Irene, marital rape by Soames, the death of Irene's lover, a long-delayed divorce, and at the end a blighted love affair between Soames daughter and Irene's son (they had both remarried).It feels like a net, I
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.030 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.007 | 0.018 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".