The everyday life of the Pskov borderland at the dawn of the Peter the Great era
Bibliographic record
Abstract
The subject of the study is the daily routine of the Pskov border region in the description of foreign travelers who visited the Russian state at the beginning of the reign of Peter the Great. The testimonies of travelers, diplomats and the military allow to trace the first changes related to the road infrastructure, the attitude towards foreigners and the way of life of the local population observed in the last quarter of the XVII century. The impression that the Pskov road made on travelers often left its indelible imprint on the entire perception of the Russian state by foreigners, and through numerous letters, diaries and reports, the image of Russia in Europe was laid on the eve of large-scale Peter's reforms. Up until the beginning of the Great Northern War, the foundation of St. Petersburg and the expansion of the borders of the Russian state, the roads of the Pskov border played an extremely important role in maintaining contacts with European countries, which led to increased attention to them both from the tsarist administration and foreign travelers. The quality of roads and related infrastructure in the border region continued to improve during the period under review. Travelers compared the sections of their route to the roads after crossing the border. Many foreign travelers noted the best quality of the road in the possessions of the Russian tsar in comparison with Polish and even Swedish possessions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| 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".