Swedish Livonia in the accounts of foreign travelers in the second half of the 17th century
Bibliographic record
Abstract
The publication examines the formation of the image of Swedish Livonia in the accounts of foreign authors from Western Europe who visited the region in person in the second half of the 17th century. During the period of Swedish dominance and the abolition of the old English privileges of the Muscovy Company, the Baltic region increasingly attracted the attention of the English and Dutch. Thanks to the accounts of Patrick Gordon, a Scottish officer in Russian service, and participants in the Earl of Carlisle's embassy to the courts of the Russian, Swedish, and Danish monarchs, it is possible to reconstruct the general perceptions of English subjects of Sweden's Baltic possessions. These accounts correlate with the accounts of Dutch diplomats who visited Swedish Livonia during the same period. Having visited the province, the authors compiled vivid and pithy descriptions not only of everyday life on the road and the region's natural environment, but also their thoughts on the customs of the local population, the prospects for trade development, and the defense capabilities of Swedish Livonia in the face of its eastern neighbor. A comparative analysis, by comparing the accounts of English and Dutch authors, allows us to create a relatively coherent image of the Swedish possessions in Livonia, as they were seen in Britain and the Republic of the United Provinces during the period of Swedish great power. The Baltic possessions of the Swedish crown are presented as a region that is relatively backward and unpopulated, but not without natural resources. The defenses of Swedish Livonia are weak, with Riga serving as the main fortress, simultaneously serving as the main center of trade and Swedish dominance in the region. It is Riga that the English and Dutch perceive as a truly European city, compared to the poor, semi-wild, and barbaric province. Despite the devastation of the Russo-Swedish War of 1656–1658, the region quickly recovered. However, it clearly lacks the attention it deserves, with road infrastructure development, the modernization of fortresses, and the construction of new fortifications neglected. The local population was subjugated by the Swedes and even economically leaned more toward the neighboring Russian state.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".