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Record W1568200203 · doi:10.1111/rest.12118

Translating as a way of writing history: <scp>F</scp>ather du <scp>C</scp>reux's <i><scp>H</scp>istoriæ <scp>C</scp>anadensis</i> and the <i><scp>R</scp>elations jésuites</i> of <scp>N</scp>ew <scp>F</scp>rance

2015· article· en· W1568200203 on OpenAlexafffund
Amélie Hamel

Bibliographic record

VenueRenaissance Studies · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsUniversité de Montréal
FundersFonds de recherche du Québec – Nature et technologiesSocial Sciences and Humanities Research Council of Canada
KeywordsNarrativeTone (literature)AdventureAudience measurementContext (archaeology)HistorySource textLiteratureAppealOrder (exchange)ArtMedia studiesClassicsArt historySociologyPolitical scienceLawSocial science

Abstract

fetched live from OpenAlex

The Historiæ Canadensis, seu Nouæ‐Franciæ libri decem, ad annum vusque Christi MDCLVI is a translation commissioned by the Society of Jesus in France in order to disseminate information concerning its evangelical activities in New France in the first decades of the seventeenth century. The source text is a series of reports written by the Jesuit missionaries in simple, unadorned French prose and printed hastily and cheaply. The form is that of a travel narrative and the tone is often grim. In 1664, Father François du Creux, a Jesuit, rewrote some of these texts, producing what might be called a three‐dimensional ‘translation’ effecting their form, language, and material features. This article explores the ways in which he restructured and reorganized the individual missionary adventures into a historical, narrative framework and turned the French text into Latin, enriching it and elevating the tone as he did so. It also discusses the manner in which expensive engravings illustrating the narratives synthesized them by providing a context and an edifying dimension. Our study demonstrates how these features transform the Relations by combining to give the translation a certain ‘gravitas’, thus widening its appeal and extending its message to a new, larger, and more varied readership.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.987
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0060.010
Scholarly communication0.0090.005
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.002

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 head0.045
GPT teacher head0.240
Teacher spread0.195 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2015
Admission routes2
Has abstractyes

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