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Record W4320352016 · doi:10.16995/dm.8195

Documentary Formulae as Text Reuse Templates: Constat and Manifestus Clauses in Early Medieval Latin Charters

2023· article· en· W4320352016 on OpenAlexvenueno aff
Timo Korkiakangas

Bibliographic record

VenueDigital Medievalist · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsReuseComputer scienceScalabilityLatin AmericansLinguisticsPhilosophyDatabaseEngineering

Abstract

fetched live from OpenAlex

This paper seeks to develop a digital diplomatic approach for reducing medieval charters’ documentary formulae into text reuse templates that represent their variational subtypes. The paper also tests this approach by visualizing the variation of two, partly mutually competing, formulae. The research data consists of 1,024 constat and manifestus clauses extracted from Latin charters written in Tuscany in the eighth to tenth centuries. Charters largely consist of formulae, which are prefabricated semi-fixed expressions of juridical content and recur in varying forms in charters of the same type. The complex interplay of documentary text reuse elements in time and place can be used to investigate historical drifts of documentary production and underlying administrative and cultural changes. The computer-assisted text reuse approach proposed is expected to be applicable to large datasets and scalable to other historical contexts.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.042
GPT teacher head0.278
Teacher spread0.236 · 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
Published2023
Admission routes1
Has abstractyes

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