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Record W3202038214 · doi:10.1163/15700658-bja10021

Who Owned Florence?: Religious Institutions and Property Ownership in the Early Modern City

2021· article· en· W3202038214 on OpenAlexaff
Justine Walden, Nicholas Terpstra

Bibliographic record

VenueJournal of Early Modern History · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsProperty (philosophy)CensusOrder (exchange)ContemplationPower (physics)HistoryBusinessSociologyPolitical scienceGeographyDemographyFinanceTheologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract This study employs a 1561 tax census to survey estimated property incomes in Florence with particular attention to lay and ecclesiastical religious institutions. Its key findings are five. First, religious institutions were collectively the wealthiest corporate entities in the city, holding one fifth of all residential properties and one third of all workshops, and drawing 20.2 percent of all property income generated within city walls. Second, many were civic- and lay-religious institutions such as confraternities and hospitals. Third, the property income of religious houses was distributed across multiple organizations while that held by the Florentine diocese was concentrated in a few. Fourth, among religious orders, Mendicant houses had a larger urban presence than the older contemplative houses. Fifth, the property holdings of the formally defunct military-religious order of the Knights of S. Jacopo signal the deftness with which some institutions adapted to new circumstances. Overall, this survey of property incomes helps quantify the shape of power in the Florentine religious universe.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score0.300

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.098
GPT teacher head0.230
Teacher spread0.131 · 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 designObservational
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

Citations3
Published2021
Admission routes1
Has abstractyes

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