Staffing provincial prisons in the first half of the 19th century (based on the materials of Northern European Russia)
Bibliographic record
Abstract
The article is devoted to the problems of staffing provincial penitentiary institutions in the first half of the 19th century. The study was based on the legislation that established the procedure for assigning to the positions and the data on the condition of penitentiary institutions in Northern European Russia. The results obtained led to the conclusion that the staffing problems were solved as the penitentiary system developed and were directly dependent on the condition of the places of detention. In the first quarter of the 19th century, when the formation of the network of penal and correctional institutions was a costly and lengthy process involving the construction of buildings for them, prison superintendents were appointed only as an exception; formally, the prisoners were under the custody of the mayors, but in reality they were under the supervision of the sentries from the internal guard. The legislation of the second quarter of the 19th century paid attention to the legal status of superintendents and warders, their powers, duties, and conditions of service for the first time, gradually elaborating the requirements for candidates for these positions. Preference was given to the retired military men: to the officials holding a rank, for the vacancies of superintendents; to lower ranks from the internal guard who had retired because of wounds, for the vacancies of warders. Although from the end of the 1830s the posts of superintendents were filled on a regular basis, not every prison castle had a full complement of employees. Throughout the period under study, prison employees were not included in the staffing tables of local institutions and were regulated individually on the initiative from below. In these conditions, in its reports, the governorate administration proceeded from the needs and current tasks, without seeking to inflate the prison staff and thereby increase the tax burden on the population, since the costs of maintaining penitentiary institutions, including salaries for employees, were covered by town communities and in the event of lack of funds, by general zemstvo dues. In the 1840s, staffing issues were overshadowed by a more significant problem: in many towns, the old wooden prisons had to be replaced with new stone buildings that would correspond to the “model” project designs and requirements for the maintenance of prisoners.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".