Wissenschaftstransfer als Folge studentischer Migration am Beispiel siebenbürgischer Intellektueller im 18. Jahrhundert
Bibliographic record
Abstract
Abstract Transylvania differed in many ways from the rest of the Habsburg Empire. This was mainly because this province, bordering the Ottoman Empire, had enjoyed religious tolerance from the 16th century onwards. Most of the Protestants living in Transylvania went abroad to study at Protestant universities like Wittenberg, Halle, Göttingen and Leyden and thus escaped the Jesuit dominated education of the Habsburg universities which had become increasingly out of date in the course of the 18th century. Even a quarter of a century after the abolition of the Jesuits, and following the reforms during the period of enlightend absolutism, the Habsburg universities were still far from being first rate in most subjects. So the majority of Transylvanian Protestant priests, lawyers and physicians were educated at universites in the north of the German speaking world or in the Netherlands, thus becoming members of a scientific community which could be regarded as belonging to the best in the world of scholarship. The impact on Transylvania was enormous because many of these scholars used modern scholarship and research methods and kept close to a world of learning which was geographically so distant from Transylvania.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".