Employees of the magistrates of Priikamye in the focus of network analysis (based on materials from urban institutions of the first quarter of the 19th century)
Bibliographic record
Abstract
The article examines the composition of the Cherdyn and Solikamsk magistrates in the first quarter of the 19th century based on the analysis of administrative and financial documentation. The subject of the research is the analysis of the mechanisms of informal influence of merchant dynasties and debt obligations on the election process to the Cherdyn and Solikamsk magistrates in the first quarter of the 19th century. The author discusses in detail the influence of merchant dynasties on the formation of the magistrate, as observed in Cherdyn. The influence of debt obligations, including the issuance of "non-repayable" promissory notes as a tool for securing support from electors, is also studied, which is particularly characteristic of Solikamsk. Economic ties between elected officials, their relatives, and the trading population, as well as financial transactions with high-ranking officials that could influence the election to the magistrate, are explored. The methodology is based on a synthesis of prosopography, quantitative source studies, and network analysis. Various bodies of historical sources (magistrate meeting minutes, broker books, promissory note protest books, revision tales, and household books) were analyzed. Databases were created for each district, and graphs of economic interactions were constructed. Within the framework of the study, graphs for each city (Cherdyn and Solikamsk) were formed, and results were analyzed using centrality and clustering metrics. The scientific novelty lies in identifying two opposing models of magistrate formation: in Solikamsk – the "debt pressure" strategy, where representatives not from influential families often issued "non-repayable" promissory notes before elections to secure support; in Cherdyn – a closed system of dominance of three merchant dynasties (Valuyev, Obolensky, Kalashnikov), whose power is confirmed by a high density of intra-group ties and clustering coefficient. It has been established that election to the magistrate depended not only on entry into the economic network of an influential lineage but also on financial transactions with high-ranking officials, such as court and titular councilors, collegiate assessors, etc. The results demonstrate that urban governance in Cherdyn and Solikamsk in the first quarter of the 18th century functioned both on the basis of legislative state acts and through personal-economic connections.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".