Personnel Management in the System of Ensuring Safety and Security of the Engineering Enterprise in the Conditions of Industry 4.0
Bibliographic record
Abstract
The main purpose of the article is to study the key aspects of ensuring economic safety and security through the modernization of personnel management.At the same time, in order to achieve the goals set, the main scientific task is to model the processes of ensuring economic safety and security through the modernization of personnel management.The object of the study is the enterprises of the engineering sector of the economy.The research methodology involves the use of modern modeling methods with appropriate graphical displays.Research questions are in the disclosure of safety and security within the scope of engineering enterprises.The key method is to use graphic language technologies.The specific result is the multi-model nature of the proposed measures within the framework of safety and security engineering enterprise.According to the results of the study, the main processes of ensuring economic safety and security through the modernization of personnel management and engineering enterprise were presented in detail.The scientific novelty of the study should be considered in the presented methodological approach to ensuring economic safety and security through the modernization of personnel management.The study is limited by taking into account only the personnel management system.Prospects for further research should be devoted to ensuring the safety and security of engineering enterprises through other control systems than personnel.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".