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Record W4382401543 · doi:10.5209/elem.88016

Medidas desesperadas. Crisis de las finanzas, apropiación de las rentas eclesiásticas y construcción del Estado en el reinado de Pedro el Grande en Aragón (1276-1285)

2023· article· es· W4382401543 on OpenAlexfundno aff
Carlos Laliena Corberá

Bibliographic record

VenueEn la España Medieval · 2023
Typearticle
Languagees
FieldArts and Humanities
TopicMedieval and Early Modern Iberia
Canadian institutionsnot available
FundersUniversitat de BarcelonaUniversidad de ZaragozaEuskal Herriko UnibertsitateaUniversitat de ValènciaEgg Farmers of Canada
KeywordsHumanitiesPolitical sciencePhilosophyArtCartographyGeography

Abstract

fetched live from OpenAlex

Este artículo examina una de las medidas adoptadas por Pedro III de Aragón en la última parte de su reinado, cuando ordenó incautar los bienes de los cargos eclesiásticos que quedasen vacantes. Después de situar en su contexto esta decisión, se analiza uno de los casos en los que el rey se apropió de las rentas eclesiásticas, el breve periodo en que estuvo sin cubrir el cargo de abad de Montearagón (agosto-septiembre de 1284). Las cuentas de los bailes locales permiten observar esta apropiación y la transferencia de una parte importante de los ingresos abaciales en favor de algunos nobles para pagarles los gastos y soldadas de su participación en el asedio de Albarracín en esas fechas. Estas cuentas informan, además, sobre las características del gobierno de la Corona de Aragón en estos años y, en particular, sobre el sistema contable y financiero que sostenía el Estado.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.291
Teacher spread0.273 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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