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Record W4404686400 · doi:10.33137/confrat.v33i2.44370

Civic Religion after Trent: Confraternities and Medici State Building in Early Modern Livorno

2024· article· en· W4404686400 on OpenAlexaff
Nicholas Terpstra

Bibliographic record

VenueConfraternitas · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicReformation and Early Modern Christianity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsWorshipState (computer science)HistoryClassicsReligious lifeAncient historyStrong tiesAgency (philosophy)LawPolitical scienceSociologyReligious studiesInterpersonal tiesSocial sciencePhilosophy

Abstract

fetched live from OpenAlex

When building the new city of Livorno, the Medici were concerned as much with social and religious life as with buildings, walls, and warehouses. They drew on traditional civic religious forms, and above all confraternities, in order to advance Catholic worship while also seeking to limit Roman intervention and maintain sufficient local agency so as to allow some degree of Jewish, Muslim, and Orthodox worship in the city. We can distinguish three groups of brotherhoods by origin and function in the first century of Livorno’s expansion from the late sixteenth to the late seventeenth centuries: i) Older and existing confraternities that had gathered the local fishermen and the earliest settlers until about 1590; ii) Confraternities founded between the 1590s and the 1630s, often with direct Medici or more general Florentine influence, and focused on meeting cultic and charitable needs; and iii) Confraternities established from the 1630s to the 1670s to fulfill these needs while also organizing activities that responded to challenges and opportunities of Livorno’s particular location. Florentine civic religious models allowed the Medici to build a vibrant Catholic social framework in Livorno while keeping Tridentine ecclesiastical forces at bay, at least until the coming of the more traditionally pious Grand Duke Cosimo III in 1670.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.854
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.226
Teacher spread0.209 · 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.

Study designQualitative
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
Published2024
Admission routes1
Has abstractyes

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