Plagiarists, enthusiasts and periodical geography: A.F. Büsching and the making of geographical print culture in the German Enlightenment, <i>c</i>.1750–1800
Bibliographic record
Abstract
This article contributes to recent scholarship on the geography and history of the book by arguing for greater attention to ‘periodical geography’, which refers to the geographical knowledge contained in periodicals, and the geographies that shaped the ways periodicals were produced, circulated and read. To illustrate the potential for such work, the article discusses geographical periodicals in the context of the German Aufklärung (Enlightenment). It focuses in particular on the Wöchentliche Nachrichten von neuen Landcharten und geographischen, statistischen und historischen Büchern und Schriften (Berlin 1773–87), edited by the prominent geographer Anton Friedrich Büsching. The story of Büsching's periodical merits attention because it throws valuable light on the practical making of geography's print culture and moral economy of knowledge in the Enlightenment. Büsching's story reveals that there were competing geographies of trust, authority and credibility at work within Enlightenment geography. It reveals that Büsching's periodical played a central role in reshaping geography's moral and epistemological order in the later 18th century. In recounting this story, my broader agenda is to argue that the very periodicity and materiality of periodicals transformed the character of geographical print culture in the later 18th century.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".