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Record W2724142320 · doi:10.1093/notesj/gjx067

The Taunton Fragment begihti

2017· article· en· W2724142320 on OpenAlexaff
Elena Afros

Bibliographic record

VenueNotes and Queries · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicMedieval Literature and History
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsParticipleLinguisticsVerbLexisSentenceMeaning (existential)HistoryOld EnglishOrthographyPhilosophyComputer scienceReading (process)Epistemology

Abstract

fetched live from OpenAlex

FOR a short and exegetically simple text, the Old English translation of the Homiliary of Angers preserved in the Taunton Fragment (Taunton, Somerset County Record Office, DD/SAS C/1193/77) exhibits a remarkable number of unconventional forms.1 Despite the availability of ten Latin witnesses fully or partially overlapping with the Old English translation, it is not always possible to determine what word the scribe or translator intended.2 Three major reasons for the uncertainty about some forms are the orthographic practices of the Taunton Fragment, the use of low-frequency lexis, and the discrepancies between the Old English translation and the identified Latin versions.3 One of the forms that has so far defied a definitive explanation is begihti (8.10). None of the three analyses that have been suggested for it—a garbled form of beh̅dig, behygdig ‘anxious’; a past participle of the verb behātan ‘to promise, vow, threaten’; and a corruption of beginde, an unattested present participle of the verb bīgan ‘to bend’—fully accounts for its orthography and meaning.4 The present note proposes an alternative interpretation that derives begihti from the verb be-hyhtan ‘to trust in, place one’s hope or faith in’. This derivation is based on the Old English <h>/<g> orthographic variation and the potential misreading of the Latin participle confessus (< confiteor ‘to confess’) as confisus (< confido ‘to trust’) either in the process of translation into Old English or in the process of the transmission of the Latin version of the homiliary.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.998

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 studies0.0030.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.234
Teacher spread0.207 · 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.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2017
Admission routes1
Has abstractyes

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