Joyce's Kaleidoscope: An Invitation to "Finnegans Wake" [Review]
Bibliographic record
Abstract
Books about Finnegans Wake announce their forms with unusual regularity: skeleton keys, plot summaries, reader’s guides, first-draft versions, lexicons, gazetteers, censuses, genetic guides, annotations, and more. Every form offers a particular route through the Wake, and we hope our collective efforts add up to a cartography of possibilities. But until now we have never been issued an “invitation” to the Wake. Many readers of this journal will realize that they must have invited themselves uncouthly to the Wake long ago, and some will imagine that it is too late for invitations when one has already been at the party for so long. Indeed, Philip Kitcher’s Joyce’s Kaleidoscope seems addressed to daunted would-be readers (and to be priced for readers rather than only libraries) or to passionate enthusiasts like Kitcher himself, rather than to Joyce scholars. Because Kitcher addresses a general audience and shrinks from engaging current discussions of Finnegans Wake, Joyce scholars may find his book of limited relevance to their own critical concerns. It is, however, a work of creativity and intelligence, and rookies and veterans alike might profitably respond to its implicit imperative: répondez s’il vous plait.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".