Bibliographic record
Abstract
‘Utopia’ is a ‘medieval fantasy game … where the lowliest of peasants can become the world’s greatest heroes … Every decision, every challenge will be yours and yours alone. From a Google search of ‘Utopia’ Sometimes a neologism’s afterlife is even busier than that of its inventor. A recent Google search of ‘Thomas More’ brought 2,500,000 hits, but a search of ‘utopia’ yielded exactly 18,000,000. All those zeros! How fitting for More’s Nowhere, even though its name is now nearly everywhere, even reimagined – witness my epigraph – as a computer game combining feudalism with American get-up-and-go. What of the man who coined ‘utopia’? More’s early biographer William Roper reports that after his arraignment More told his judges (as he told others) that he and they would ‘in heaven merrily all meet together’ (Roper 250). This essay, however, will focus on More’s earthly afterlife and that of his two major works The History of King Richard the Third and Utopia . In his own day his Latin epigrams were widely enjoyed, his savage polemics roundly condemned but just as savagely answered by William Tyndale and other Reformers, and his eloquent Tower Works (particularly the Dialogue of Comfort against Tribulation ) published and, if we may judge from a few allusions, read with appreciation. But More’s later fame was shaped largely by ambivalent memories of the man, by the usurping duke of York whom he helped make an archetype of pathologically cunning tyranny, and by the famous island that gave us the word ‘utopia’, the genre of utopian fantasy, and eventually, in an expansion of More’s pun on u/eutopia, the word ‘dystopia’. It is on these three afterlives – of the person and his two most influential books – that I will focus.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.169 | 0.077 |
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".