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Record W2109748504 · doi:10.33137/rr.v31i3.9166

"Saper la mente della soa Beatitudine": Pope Paul II and the ambassadorial community in Rome (1464-71)

2008· article· fr· W2109748504 on OpenAlexvenueno aff
Paul M. Dover

Bibliographic record

VenueRenaissance and Reformation · 2008
Typearticle
Languagefr
FieldSocial Sciences
TopicHistorical Influence and Diplomacy
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceObligationArtPhilosophyLaw

Abstract

fetched live from OpenAlex

Cet article examine la pratique des ambassadeurs envoyés par les états italiens à la cour du pape Paul II (1464–71), en se concentrant en particulier sur la façon dont ils ont assumé leur rôle d’informateur. Puisque Paul était un pape instable, impénétrable et souvent inaccessible, les ambassadeurs ont souvent été dans l’obligation d’obtenir des informations au sujet du pape et de ses intentions de manière indirecte. En s’appuyant largement sur la correspondance diplomatique romaine durant le pontificat de Paul, cet article montre comment les ambassadeurs se sont construit des réseaux de contacts au sein même de la cour papale afin de s’assurer un apport continu d’informations utiles et ce, en temps voulu. Ces réseaux comptaient donc des membres de toute la communauté évoluant autour de la papauté, incluant des cardinaux bien placés, des fonctionnaires ecclésiastiques, d’autres ambassadeurs, des agents politiques, aussi bien que plusieurs informateurs des hiérarchies inférieures. Rome était, en effet, un marché de l’information, si bien que les ambassadeurs devaient utiliser toutes leurs compétences pour entrer en possession des informations les meilleures et les plus précieuses.

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 score0.093
Threshold uncertainty score0.185

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.009
Scholarly communication0.0040.002
Open science0.0000.004
Research integrity0.0020.003
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 head0.032
GPT teacher head0.293
Teacher spread0.260 · 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

Citations12
Published2008
Admission routes1
Has abstractyes

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