From Apologetics to Indology: A Case Study in the Scholarship of Roberto de Nobili, SJ
Bibliographic record
Abstract
Abstract: Roberto de Nobili (1579–1656), Jesuit missionary to India, was a pioneering scholar in Christianity's encounter with Hinduism, distinguished by personal adaptation, study of Indian religious traditions, and the composition of treatises in Tamil as well as Latin. But this incipient Indology, motivated by apologetic purposes, not only objectified Hinduism but also conferred expert status on the outside observer. This essay compares two treatises: Inquiry into the Meaning of “God” (ca. 1612) and Dispelling Ignorance (ca. 1640). They are similar in shape (an understanding of “God” elaborated in accord with various perfections), purpose (demonstrating the untenable nature of Hindu conceptions of deity), and in the deployment of locally adduced examples showing the implausibility of Hindu beliefs. Dispelling Ignorance more thoroughly objectifies India, reserving superior knowledge to the observer. It marks the path from missionary apologetics to the religiously neutral but still hegemonic Indology that followed. Today, Christian theology requires expert scholarship that is also empathetic, less prone to objectifications of other religions that disregard the self-understanding of their believers.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.025 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.006 | 0.009 |
| 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".