Bibliographic record
Abstract
Chinese Sympathies examines how Europeans—German-speaking writers and thinkers in particular—identified with Chinese intellectual and literary traditions following the circulation of Marco Polo's Travels. This sense of affinity expanded and deepened, Daniel Leonhard Purdy shows, as generations of Jesuit missionaries, baroque encyclopedists, Enlightenment moralists, and translators established intellectual regimes that framed China as being fundamentally similar to Europe. Analyzing key German literary texts—theological treatises, imperial histories, tragic dramas, moral philosophies, literary translations, and poetic cycles—Chinese Sympathies traces the paths from baroque-era missionary reports that accommodated Christianity with Confucianism to Goethe's concept of world literature, bridged by Enlightenment debates over cosmopolitanism and sympathy, culminating in a secular principle that allowed readers to identify meaningful similarities across culturally diverse literatures based on shared human experiences. This book is freely available in an open access edition thanks to TOME (Toward an Open Monograph Ecosystem)—a collaboration of the Association of American Universities, the Association of University Presses, and the Association of Research Libraries—and the generous support of the Pennsylvania State University. Learn more at the TOME website, available at: openmonographs.org. The open access edition is available at Cornell Open (cornellpress.cornell.edu/cornell-open) and other repositories.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.004 |
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".