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Record W1991523213 · doi:10.7202/009382ar

Translation in Medieval and Reformation Norway: A History of Stories or the Story of History

2004· article· en· W1991523213 on OpenAlexvenueno aff
Elizabeth Rasmussen

Bibliographic record

VenueMeta Journal des traducteurs · 2004
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsMiddle AgesLiteratureContext (archaeology)ChristianityHistoryStyle (visual arts)History of literatureClassicsArtArchaeology

Abstract

fetched live from OpenAlex

Three major events marked medieval Norwegian literary production, style, and language: the introduction of Christianity, the Black Death, and the Reformation. Foreign material in translation was pivotal to the transition between the pagan Viking Era and the Christian Middle Ages and to the passage from Catholicism to Lutheranism in the 16th century. Lack of translation and literary production following the Black Death also had an impact. Translation in a medieval and Renaissance context must be understood as transfer of knowledge, the crossing of linguistic and cultural borders. The translated texts helped introduce and consolidate the social conventions promoted by the new religion. The distinction between story and history faded. Religious and devotional material preceded the secular court literature from the French-speaking territories. Hagiographic material ran parallel to heroic tales: all genres helped illustrate the virtues of Christian life and social organization and needed only minor adaptation for a Norse audience. The pagan literary conventions blended with those of the imported material and resulted in a distinct Norse literary style. The systematic encounter with other gave rise to a new perception of self . The largely anonymous translators contributed to the inclusion of other in self , to the assimilation of foreign cultural values and concepts.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.112
GPT teacher head0.268
Teacher spread0.156 · 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 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

Citations2
Published2004
Admission routes1
Has abstractyes

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