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Record W2332171392 · doi:10.1086/ahr.115.4.1248

Giovanni Ciappelli . Fisco e società a Firenze nel Rinascimento . (Studi e testi del Rinascimento europeo, number 36.) Rome : Edizioni di storia e letteratura . 2009 . Pp. viii, 297. €38.00.

2010· article· it· W2332171392 on OpenAlexaff
Lawrin Armstrong

Bibliographic record

VenueThe American Historical Review · 2010
Typearticle
Languageit
FieldEconomics, Econometrics and Finance
TopicItaly: Economic History and Contemporary Issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFifteenthState (computer science)DebtArtHumanitiesPoliticsHistoryClassicsPolitical scienceLawEconomics

Abstract

fetched live from OpenAlex

The public finances of late medieval Florence are better documented than those of any other medieval European state. As Giovanni Ciappelli remarks in this collection of his essays on Florentine political economy, the records of the republic's funded debt, the monte comune, preserved in the Florentine state archive alone comprise some 4000 registers. But they represent only part of the evidence: Anthony Molho and Elio Conti were able to produce their pioneering studies without access to the monte archive, which was long closed for want of an inventory. It was Molho's initial survey of the deposit in 1971–1972 that first allowed scholars to navigate this ocean of data, and Ciappelli himself is collaborating on a fresh inventory. As the essays in this volume confirm, the debt dominated virtually every aspect of Florentine political economy from at least the beginning of the fifteenth century to the end of the republican period.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.370
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0030.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.018

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 head0.026
GPT teacher head0.245
Teacher spread0.219 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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
Published2010
Admission routes1
Has abstractyes

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