“To find God in all things”: the meeting of faith and mathematics in Jesuit education during the scientific revolution
Bibliographic record
Abstract
ResumoÉ bem conhecido e aceito que o início da tradição matemática dos jesuítas se deve a Christopher Clavius, professor de Matemática no Colégio Romano entre 1567 e 1595. Neste artigo, questiona-se: Quais eram os aspectos sociais, políticos, filosóficos, e as razões religiosas que levaram Clavius a criar um currículo educacional inovador que incluiu o ensino de matemática nas faculdades jesuítas? Para responder à esta pergunta, olhamos para os primeiros anos da Companhia de Jesus considerando o contexto histórico e uma análise de como o aprendizado matemático interagiu com a doutrina Católica.Palavras-chave: Pedagogia Jesuítica; Ciência e Fé; Igreja e ciência AbstractIt is well known and accepted that the beginning of the mathematical tradition of the Jesuits is due to Christopher Clavius, professor of Mathematics in the Roman College between 1567 and 1595. In this article, the question is: What were the social, political, philosophical, and religious reasons that lead Clavius to create an innovative educational curriculum that included the teaching of mathematics in the Jesuit colleges? To answer this question, we look at the early years of the Society of Jesus considering the historical context and an analysis of how mathematic learning interacted with the Catholic doctrine.Keywords: Jesuit pedagogy; science and faith; Church and science
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.029 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.008 |
| 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".