Bibliographic record
Abstract
Of all the many Anglo-Saxons who travelled to the Continent, some never to return, Boniface, apostle to the Germans, arguably had the deepest and most enduring inuence; for some, he is simply ‘the greatest Englishman’. But aside from Boniface's historical importance there is much of related interest for scholars of Anglo-Saxon literary culture too: not only does a wealth of hagiographical material survive relating to Boniface and his mission, but there remain a number of letters, poems, and other works written by Boniface himself, alongside a wide range of associated texts. Yet while the literary contexts and merits of (for example) Boniface's poetry have been discussed a number of times in recent years, the primary academic focus on the so-called ‘Bonifatian correspondence’ has tended to be historical, rather than literary. Such a focus has tended to privilege those letters with political or administrative implications above those that deal with more domestic or personal issues, yet it is precisely the latter category which shows the less formal aspects of Anglo-Saxon literary culture, and seems to invite closer comparison with a range of other texts. In particular, the innately repetitious and formulaic quality of much of the correspondence has much in common with that of several other areas of Anglo-Saxon literature in both Latin and Old English, whether in prose or verse, and this article seeks to explore those links in detail, in order to offer a broader literary context for the composition of the correspondence as a whole.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.119 | 0.020 |
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".