Sources of Population Records of Early Yekaterinburg: Peculiarities and Information Potential
Bibliographic record
Abstract
This article studies the demographic history of Yekaterinburg in the second quarter of the eighteenth century. The authors focus on the population changes in the city between 1723 and 1744. This issue remains relevant since currently, there are no books or articles that would provide consistent data on the number of residents who settled near the Yekaterinburg plant. The analysis of historiography demonstrates that a significant part of scholars provide information about the composition and population of the city only for some years of its existence, without explaining the features of the primary sources underlying their research. This, in turn, has led to the fact that historians are split when it comes to estimates of the population of the fortress factory in the first years of its existence. In connection with the celebration of the city’s tercentenary, the researchers’ appeal to the history of the population of Yekaterinburg in the second quarter of the eighteenth century becomes even more significant. The work aims to analyse the features and information capabilities of primary sources containing data on the population of the fortress and plant. The main research methods include methods of primary source studies. In addition, the authors use the comparative method and method of system analysis, as well as the method of diachronic analysis. Employing these methods, the authors establish the approximate number and reconstruct the composition and main groups of residents of the future city. Also, they demonstrate that along with national censuses, the mining administration exercised police control over the structure and population numbers to solve various tasks. Among them are the organization of production processes, the defence of factories during the Bashkir uprising of 1735–1740, control over the population on the territory of the city, etc. One of the results of the study is the clarification of the male population of Yekaterinburg. Comparison of data from different years helps draw conclusions about the positive dynamics of the number of inhabitants in the first decades of the city’s existence. The increase in the figures and change in the composition of the population affected the appearance of the settlement. It acquired urban features. Thus, in the second quarter of the eighteenth century, there were all the prerequisites for Yekaterinburg to acquire the status of a city.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.012 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".