IDEAS, INSTITUTIONS, AND <i>WISSENSCHAFT</i>: ACCOUNTING FOR THE RESEARCH UNIVERSITY
Bibliographic record
Abstract
Theodore Ziolkowski, Clio the Romantic Muse: Historicizing the Faculties in Germany (Ithaca and London: Cornell University Press, 2004) Thomas Albert Howard, Protestant Theology and the Making of the Modern German University (Oxford: Oxford University Press, 2006) William Clark, Academic Charisma and the Origins of the Research University (Chicago and London: University of Chicago Press, 2006) In the same symbolic way that the modern political world can be traced to revolutionary Paris, and the modern economic world to industrial Manchester, so modern academia and modern scholarship trace their origins to Germany at the turn of the nineteenth century. There and then the study of history, philosophy, philology, linguistics, and, somewhat later, the natural sciences was transformed in content and methodology onto the lines that would characterize them until deep into the twentieth century. Some argue that the period from 1770 to 1830 launched a still more fundamental transformation in the very structure of academic knowledge: the creation of modern “disciplines” as the new social and intellectual forms through which knowledge would be classified, produced, and communicated.
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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.007 | 0.037 |
| Scholarly communication | 0.023 | 0.031 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".