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Record W4403314236 · doi:10.1515/9781802702064-009

Chapter 4 ALDHELM’S AENIGMATA AND THE TEACHING OF LATIN PROSODY

2024· book-chapter· en· W4403314236 on OpenAlexaff
Cameron Scott Laird

Bibliographic record

VenueAmsterdam University Press eBooks · 2024
Typebook-chapter
Languageen
FieldArts and Humanities
TopicMedieval and Classical Philosophy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProsodyLinguisticsPsychologyPhilosophy

Abstract

fetched live from OpenAlex

it is a curious fact that so much of the earliest Anglo-Latin poetry should have been riddles.Some 270 verse riddles were composed, mostly during the late seventh or eighth centuries, and their authors were some of the most learned and esteemed men of the age, including Aldhelm, Bishop of Sherborne (ca.705-710/11), the Venerable Bede (ca.672-735), Tatwine, Archbishop of Canterbury (ca.731-34), Boniface, Archbishop of Mainz (ca.745-54), and Alcuin of York (ca.735-804). 1The immediate and immense popularity of the riddle as a poetic genre in England arose out of the first AngloLatin collection: Aldhelm's Aenigmata, which was probably also the first major metrical work by someone who learned Latin as a distinctly foreign language. 2Aldhelm sent his Aenigmata, together with his own metrical treatises, to Aldfrith, King of Northumbria (r.685-705). 3 His purpose was apparently to help others understand Latin metre by exemplifying the rules of versification expounded by the metrical tracts in a series of short, memorable poems in the form of riddles.The traditional chrono logy of Aldhelm's works does not seem to support the idea that he intended his Aenigmata to be teaching texts.Aldhelm probably composed his riddles long before either metrical treatise, even circulating a version of them before their publication alongside these didactic works. 4 This early version has in fact survived in a few continental manu-1 For all these Latin riddles, see Orchard, The Old English and Anglo-Latin Riddle Tradition, 1:1-291, 2:1-313.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.908
Threshold uncertainty score0.776

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.197
Teacher spread0.153 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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