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Seville

2022· reference-entry· en· W4307204155 on OpenAlexaff
Guy Lazure

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldArts and Humanities
TopicHistorical Art and Architecture Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsProsperityPopulationHumanismMonopolyGeographyState (computer science)PeninsulaEconomic historyHistoryPolitical scienceEconomySociologyLawDemographyArchaeology

Abstract

fetched live from OpenAlex

With the opening of the New World and the monopoly on trade granted to the city starting in 1503, early modern Seville went from a relatively important regional commercial center to a major continental and even international metropolis whose population nearly doubled every fifty years. This newfound prosperity had a transformative impact not only on the local economy but on internal social dynamics as well, given the number of migrants the city attracted, the diversity of their origins, and the social mobility this sudden influx of capital facilitated. In a place where stories of rags to riches (and riches to rags) abounded and living conditions varied significantly, scholars have naturally paid considerable attention to the social and economic disparities between and within groups or classes of residents. Religion was also at the heart of early modern Sevillian life with the presence of significant communities of converted Jews and Muslims, as well as the discovery of one the largest Protestant “flare-ups” in Spain, that set off the combined repressive efforts of the Spanish state and the Inquisition. But 16th- and 17th-century Seville was not only the “gateway to the Indies” or the “great Babylon” that poets, playwrights, and travelers have described for centuries. It was also one of the greatest and most vibrant centers of art, learning, letters, and print culture on the Iberian Peninsula, home to some of Golden Age Spain’s most illustrious writers, humanists, and painters.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.227
Threshold uncertainty score0.841

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.2270.001

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 head0.037
GPT teacher head0.223
Teacher spread0.186 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2022
Admission routes1
Has abstractyes

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