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Record W2599928006 · doi:10.1515/9781474402248

Secretaries and Statecraft in the Early Modern World

2016· book· en· W2599928006 on OpenAlexaboutno aff
Paul M. Dover

Bibliographic record

VenueEdinburgh University Press eBooks · 2016
Typebook
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHistory

Abstract

fetched live from OpenAlex

An illuminating exploration of the role played by state secretaries in shaping inter-state relations in early modern Eurasia One of the prominent themes of the political history of the 16th and 17th centuries is the waxing influence officials in the exercise of state power, particularly in international relations, as it became impossible for monarchs to stay on top of the increasingly complex demands of ruling. Encompassing a variety of cultural and institutional settings, these essays examine how state secretaries, prime ministers and favourites managed diplomatic personnel and the information flows they generated. They explore how these officials balanced domestic matters with external concerns, and service to the monarch and state with personal ambition. By opening various perspectives on policy-making at the level just below the monarch, this volume offers up rich opportunities for comparative history and a new take on the diplomatic history of the period. Contributors Rayne Allinson, University of Michigan-Dearborn, USA Rebecca Boone, Lamar University in Texas, USA Paul M. Dover, Kennesaw State University, USA Rajeev Kinra, Northwestern University, USA Isabella Lazzarini, University of Molise, Italy Russell E. Martin, Westminster College in New Wilmington, PA, USA Colin Mitchell, Associate Professor of History at Dalhousie University Toby Osborne, University of Durham, UK David Parrott, New College, University of Oxford, UK Daniel Riches, University of Alabama, USA Franz A. J. Szabo, University of Alberta, Canada Erik Thomson, University of Manitoba, Canada Megan K. Williams, University of Groningen, Netherlands

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)0.000
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: Other · Consensus signal: Other
Teacher disagreement score0.956
Threshold uncertainty score0.949

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
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 head0.024
GPT teacher head0.238
Teacher spread0.214 · 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
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

Citations1
Published2016
Admission routes1
Has abstractyes

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