Janet Schrunk-Ericksen, <i>Reading Old English Biblical Poetry: The Book and the Poem in Junius 11.</i> Toronto: University of Toronto Press, 2021, pp. 222.
Bibliographic record
Abstract
Abstract Janet Schrunk-Ericksen (Ph.D., University of Illinois), Professor of English and Acting Chancellor at the University of Minnesota, Morris, has written a worthwhile study of Oxford, Bodleian Library MS Junius 11 and key aspects of the five narrative poems within it. As her title suggests, the five poems might have been considered “the poem”: one poem with multiple parts, by an early reader reading through the book, if proceeding sequentially. Indeed, Schrunk-Eriksen’s book, Reading Old English Biblical Poetry, explores how early readers may have approached and understood Junius 11, its sequential contents, and its representation of God’s divine power. She pays careful attention to the physical codex as well as to close readings of the poems. Her work emerges alongside an on-going revival of academic interest in how to read medieval manuscripts, which is similarly demonstrated by Elaine Traherne’s study, Perceptions of Medieval Manuscripts: The Phenomenal Book (Oxford, 2022) and Carl Kears, MS Junius 11 and its Poetry (Boydell & Brewer, 2022).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".