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Record W2243374416 · doi:10.82308/20019

Ivan IV et la consolidation du pouvoir muscovite dans l'historiographie russe du XIXe siècle

2013· article· fr· W2243374416 on OpenAlexfundno aff
Alexandre Benoit

Bibliographic record

VenueeScholarship@McGill (McGill) · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicSoviet and Russian History
Canadian institutionsnot available
FundersMcGill University
KeywordsHumanitiesEmpireHistoriographyArtReignContext (archaeology)EthnologyPoliticsHistoryAncient historyPolitical scienceLawArchaeology

Abstract

fetched live from OpenAlex

Le tsar Ivan IV, surnommé le Terrible, fut un personnage qui devint rapidement un symbole pour l'identité nationale russe. Dès la création de l'Empire russe par Pierre le Grand, il fut reconnu comme celui qui a consolidé le territoire de la Moscovie au XVIe siècle et a centralisé son pouvoir contre les velléités d'une élite à conserver ses privilèges. Cependant, la construction de ce récit historique fut un long procédé, limité par la rareté des sources et les conventions étatiques. Cette thèse visait à analyser comment quatre historiens clés de la Russie impériale construisirent les connaissances historiques sur Ivan. Les écrits de Nikolai Karamzin, Sergei Soloviev, Vasilii Kliuchevskii et Sergei Platonov seront pris en compte pour comprendre le processus derrière l'historiographie de la seconde partie du règne d'Ivan, caractérisée par une cruauté et par la consolidation de son pouvoir. Cette analyse démontre l'influence que les expériences personnelles de l'historien, ses croyances et le contexte socio-politique sur la construction de cette période jugée capitale pour l'État russe.

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)0.001
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 score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.005
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.235
Teacher spread0.222 · 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
Published2013
Admission routes1
Has abstractyes

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