Bibliographic record
Abstract
When the editors were considering a suitable topic for this festschrift they found themselves, as one might expect with an honorand of Barrie Dobson's range of interests, spoilt for choice. It was Sarah Rees Jones who came up with the theme of Utopias and Idealists, which pays tribute both to Barrie's strong interest in social justice, reflected in his work on the Peasants' Revolt and Robin Hood, and also to his long-standing engagement with the aspirations and achievements of medieval communities and their administrators, both ecclesiastical and secular. This wide range of interests, to which John Taylor pays proper tribute below, has equipped Barrie with a special understanding of the relationship between idealism and pragmatism that has informed his equally long-standing interest in the life and work of Thomas More. The initial hope was that this would be a subject that would draw together contributions from modernists as well as medievalists. That, sadly, foundered. Collections of papers ranging from the early Middle Ages to the twentieth century are not thought viable publishing ventures these days. Several of Barrie's friends and colleagues who had hoped to contribute were accordingly unable to do so, and the choice of topic (and the need to keep the collection within reasonable length) excluded others. Those friends and colleagues of Barrie whose papers are included here are conscious that they stand for a great many others who wished to be involved, and whose good wishes go with them.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.415 | 0.267 |
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".