Information resources for the reconstruction of the collective portrait of the headquarters of the 316th rifle division in 1941
Bibliographic record
Abstract
The article talks about the author’s search work for staff of the headquarters of the first body of the 316th rifle division in 1941 in the battle of Moscow. The goal: based on the open archives of Russia and Kazakhstan in 2017, to give an analysis of the personal data of staff employees of 1941. Methods: Methodology of comparative-historical research, methodology and technique of socio- logical research, comparative-historical method and analysis of statistical data, etc. Take advantage of interdisciplinary methodology, content analysis, and qualitative document analysis. Based on the study of only recently discovered data for researchers, a number of important conclu- sions that refute the opinions voiced in the twentieth and early 21st centuries were made. The headquar- ters included representatives of 6 nationalities of the country. More than a quarter of the headquarters were non-partisan people. 77.8% of commanders with higher and secondary education worked at the headquarters. 54.2% of staff employees did not have a military education, which is one of the reasons why the division was called militia. The division served as a bridgehead for the offensive operations of the Moscow battle, which drove the enemy hundreds of kilometers from the capital. The practical significance of the study is the possibility of using its results in the field of culture and history. The results of the study can be integrated into educational processes. Tips and recommendations are given to journalists and PR specialists on how to cover topics based on the search for archival materials and its analysis. Materials can be included in history, journalism and public relations textbooks of the twentieth century. Key words: 316 rifle division, Central Archive of the Ministry of Defense of Russia, Central Archive of the Republic of Kazakhstan, journalists, archive works coverage in media.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.158 | 0.044 |
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".