Tristan Major, <i>Undoing Babel. The Tower of Babel in Anglo-Saxon.</i> Toronto Anglo-Saxon Series, 25. Toronto, Buffalo and London: Toronto University Press, 2018, xiii, 289pp.
Bibliographic record
Abstract
This is an interesting and important study both in its broader implications and on a specific level as a series of case studies (thus p. 237) of Anglo-Saxon texts. The principal title is significant: the narrative of Babel in the early part of Genesis resulted in the division of languages. On the face of it, this is a negative result, and the instigator of the building of the fateful tower, usually taken to be Nimrod, himself sometimes seen as a giant and indeed an idolater, is condemned. Against the Genesis tale, however, is set typologically the positive account in Acts 2: 1–13 of the gift of tongues, with the underlying notion of the unifying role of the Church in bringing together the new diversity in mankind. Luke 10: 1 and also Numbers 11:16–25 are also relevant to the number of languages. The chapters of Genesis which contain the brief story of the tower also contain what is known as the table of nations, the dispersal of Noah’s descendants, which becomes of great significance in the context of myths of national origin. Major presents the reflection in Anglo-Saxon texts – and it is a notably varied one – of the way the linguistic diversity is presented, with the emphasis on the unification through Christianity of the separated nations and tongues, and of the perceived position and role of English. Some traditions, incidentally, make a distinction between pagan and Christian languages; Jans Enikel’s later rhymed German chronicle, for example, lists one of the languages after Babel as “heathen.”
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".