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Record W3153637193 · doi:10.16922/bloodlandpower

Blood, Land and Power: The Rise and Fall of the Spanish Nobility and Lineages in the Early Modern Period

2021· book· en· W3153637193 on OpenAlex
Manuel Pérez-García

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueUniversity of Wales Press eBooks · 2021
Typebook
Languageen
FieldArts and Humanities
TopicSpanish Literature and Culture Studies
Canadian institutionsCentre for Global Health Research
FundersMinisterio de Economía y CompetitividadJunta de AndalucíaEuropean CommissionUniversity of Leeds
KeywordsNobilityHonourPeriod (music)ChronologyRivalryHistoryPower (physics)PoliticsMiddle AgesGenealogyEstateAncient historyGeographyArchaeologyPolitical scienceLawArtAesthetics

Abstract

fetched live from OpenAlex

The analysis of land management, lineage and family through the case study of early modern Spanish nobility from sixteenth to early nineteenth century is a major issue in recent historiography. It aims to shed light on how upper social classes arranged strategies to maintain their political and economic status. Rivalry and disputes between old factions and families were attached to the control and exercise of power. Blood, land management and honour were the main elements in these disputes. Honour, service to the Crown, participation in the conquest and ‘pure’ blood (Catholic affiliation) were the main features of Spanish nobility. This book analyses the origins of the entailed-estate (mayorazgo) from medieval times to early modern period, as the main element that enables us to understand the socio-economic behaviour of these families over generations. This longue durée chronology within the Braudelian methodology of the research aims to show how strategies and family networks changed over time, demonstrating a micro-history study of daily life.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score0.603

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.167
Teacher spread0.154 · 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