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Record W3152708656 · doi:10.33137/rr.v43i4.36386

Patronage and Power: The Vicereines at the Court of Naples in the Reign of Philip III of Spain

2021· article· en· W3152708656 on OpenAlexvenueno aff
Alejandra Franganillo Álvarez

Bibliographic record

VenueRenaissance and Reformation · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Spain
Canadian institutionsnot available
Fundersnot available
KeywordsReignMonarchyPoliticsSisterPower (physics)HistoryHumanitiesLawGenealogyAncient historyClassicsPolitical scienceArt

Abstract

fetched live from OpenAlex

Recently, several studies have focused on the figure of the viceroy in the Spanish Monarchy, especially in the Kingdom of Naples. However, far less attention has been paid to the role of the vicereines of Naples. The goal of my study is to investigate and clarify the significant roles held by these noblewomen at one of the most important viceregal courts of the Spanish Monarchy. I will focus on one vicereine in particular, Catalina de Zúñiga y Sandoval, 6th Countess of Lemos and sister to the Duke of Lerma (1599–1601), who developed an extensive political network through copious correspondences, requesting and distributing mercedes (dignities and favours) among family members and her clientage. A revisionary analysis of the vicereines’ roles at the Neapolitan court demonstrates how knowledge of their political contribution is essential for a deeper understanding of the economic and political strategies deployed by their families.

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)0.002
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 score0.157
Threshold uncertainty score0.312

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.010
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.002
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 head0.018
GPT teacher head0.214
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

Citations2
Published2021
Admission routes1
Has abstractyes

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