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Record W2123020622 · doi:10.1353/fch.2003.0019

Borderland Worries: Loyalty Oaths in Acadie /Nova Scotia, 1654-1755

2003· article· fr· W2123020622 on OpenAlexaboutno aff
Anna Johnston

Bibliographic record

VenueFrench Colonial History · 2003
Typearticle
Languagefr
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaHumanitiesPolitical scienceArtEthnologySociology

Abstract

fetched live from OpenAlex

A l'époque moderne, les rois et leurs officiers s'inquiétaient de la fidélité de leurs sujets à la couronne. Pour adresser ce souci, ils utilisaient souvent des serments. Une histoire bien connue relate comment, dans la région frontière de l'Acadie/Nova Scotia entre 1713 et 1755, les autorités britanniques à Annapolis Royal et à Halifax essayaient de convaincre les Acadiens à jurer un serment de fidélité inconditionnelle, une tentative qui se termina avec la déportation massive de milliers d'Acadiens à partir de 1755. Cet article ne se concentre pas sur cet épisode familier, mais sur maints autres serments de fidélité appliqués ou discutés pendant la période tourmentée entre le milieu du dix-septième siècle et le milieu du dix-huitième. Les Britanniques n'étaient pas le seul pouvoir à utiliser des serments ou à penser à les employer vis-à-vis des Acadiens; les gens de la Nouvelle-Angleterre et les Français eux-mêmes en faisaient autant. Pendant un siècle, par conséquent, la fidélité des Acadiens se trouvait le sujet d'une attention profonde de la part de toutes les autorités impériales.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.002
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.018
GPT teacher head0.235
Teacher spread0.217 · 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

Citations10
Published2003
Admission routes1
Has abstractyes

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