Claiming Nobility in the Monarquía Hispánica: The Search for Status by Inca, Aztec, and Nasrid Descendants at the Habsburg Court
Bibliographic record
Abstract
By the early seventeenth century, petitioners at the royal court in Madrid who claimed descent from the Inca rulers of Peru, the Aztec rulers of Mexico, and the Nasrid emirs of Granada found ways to acquire noble status and secure rights to their ancestral lands in the form of entailed estates. Their success in securing noble status and title to their mayorazgos (entailed estates) rested on strategies, used over the course of several generations, that included marriages with the peninsular nobility, ties of godparentage and patronage, and military service to the crown. This article will examine the networks formed in Madrid between roughly 1600 and 1630 when the descendants of the Inca and Aztec rulers interacted with peninsular noble families at court, obtaining noble status and entry into the military orders and establishing their mayorazgos. Their strategies for claiming nobility show striking parallels to those adopted by the Morisco nobility, and one aim of this article is to suggest how knowledge of such strategies circulated among families both at the royal court in Madrid and in the viceroyalties of New Spain and Peru.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".