Bibliographic record
Abstract
Abstract Between 1572 and 1575, a man named Diego litigated for his freedom from slavery in several Spanish courts. Identified as an Indio (Indian), he claimed to have been born in the Spanish territory of Liampo (now Ningbo), China, and later carried on a Spanish ship to Mexico, and eventually to Seville. His master, the cleric Juan de Morales, asserted that he had bought Diego in Portuguese Goa and taken him to Mozambique and to Lisbon before finally bringing him to Seville. At issue was whether Diego was a Portuguese or Spanish imperial subject, since Spanish law strictly prohibited the enslavement of Indios in Spanish territories, while Portuguese laws did not. As witnesses (several of them former slaves from disparate locations including Panama, Lima, Goa, Mozambique, and China) tried to determine Diego’s imperial status, not only did they reveal their comparative fantasies about Portuguese or Spanish landscapes, but they also embedded their own diasporic tales of liminality and loss into Diego’s. Here is the ultimate example of the Indio experience in Castile: an attempt to affix imperial boundaries to a construct that was, in itself, a metaphor for how the rapidly changing globe was imagined, experienced, and compartmentalized. The use of the increasingly amorphous cultural label ‘Indio’ in Castile was symptomatic of tensions between imperial regimes’ desire to constitute and reify themselves as bounded entities and the global mobilities of some of the most marginalized subjects who informed those processes.
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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 | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".