De talen van de evangelisatie: De vroegmoderne circulatie van kennis door missionarissen over de inheemse talen van Nieuw-Spanje, Peru en Nieuw-Frankrijk
Bibliographic record
Abstract
Not long after the first European explorations of the Americas religious orders set out to evangelize the natives inhabiting these territories across the other side of the Atlantic Ocean. Missionaries operating in the (for them) unknown and vast lands all faced similar challenges when establishing contact with local communities. The language barrier presented enormous and one of the most important obstacles to European religious men attempting to convert local indigenous peoples to the Christian faith. In order to teach the religious doctrine to native groups of people unfamiliar with European culture and religion efficiently, missionaries did not impose European languages but sought to learn these local tongues in order to utilize them as languages of evangelization. To foster the continuation of the mission, missionaries eagerly codified their acquired knowledge on these languages. They compiled grammars and vocabularies to facilitate the study of these languages, investigating the grammatical structures and listing words. They also created copious translations of devotional texts, such as catechisms, sermon books and confession manuals, to use as a references guide when addressing indigenous peoples orally. This initiated an ever-developing process in which they accumulated, codified and distributed knowledge on the large variety of languages spoken in the Americas. These missionary tools are the focus of the current work, which, as a part of the multidisciplinary project "Evolving views on world's languages in a globalizing world (1540-1840)", outlines the circulation of missionary knowledge on these languages, by examining the universal patterns underlying early modern missionaries' language study in the Americas and their subsequent efforts to produce and distribute knowledge of indigenous languages on paper. The dissertation studies three different areas during the first two centuries of colonization: New Spain and Peru, two viceroyalties of the Spanish empire, and New France, the French colony in present-day Canada. This study devotes particular attention to the discourse missionaries employed when discussing their linguistic activities and seeks to gain a better understanding of the material and social nature of the indigenous-language documents they produced by bringing into play a (book) historical approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".