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French and Canadian Jesuit History Writing

2019· reference-entry· en· W2952952504 on OpenAlexaffabout
Adina Ruiu

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHistoriographyHistoryOrder (exchange)National historyLiteratureWorld historyClassicsArtArchaeologyLawAncient historyPolitical sciencePolitics

Abstract

fetched live from OpenAlex

This chapter investigates the links between the “old” and the “new” Society, as forged through the writing of history. More specifically, it focuses on the historiographical methods that were theorized and put into practice by French and Canadian Jesuit historians, active between the 1830s and the 1920s, in studying the history of their seventeenth- and eighteenth-century predecessors, with special attention to the writing of the history of the Canadian missions. The bibliographical and historiographical laboratory from which inventories (and categories) of sources, as well as general or specialized studies, were produced emerges by looking at both the correspondence of Jesuit historians and missionaries and their published works. Thus are revealed the constraints weighing on historical projects, the overlap between different objects and scales of analysis (the general history of the Order; histories of assistancies, missions, residences, etc.; the relationship with national history and history of empires), the blurred boundaries between hagiography and history (especially within the genre of life writing), and the necessary adjustments to different readerships.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.066
Threshold uncertainty score0.480

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0070.010
Science and technology studies0.0170.004
Scholarly communication0.0070.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0240.001

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 head0.039
GPT teacher head0.198
Teacher spread0.159 · 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
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
Published2019
Admission routes2
Has abstractyes

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