Modelling Information Systems for Personnel Management: Navigating Economic Security in the Transition to Industry 5.0
Bibliographic record
Abstract
Within the backdrop of rapidly advancing technology, the transition from Industry 4.0 to Industry 5.0 is underway, with each socio-economic system endeavoring to adapt to these transformative changes.Industry 5.0 signifies a shift from conventional technologies, advocating for enhanced digital interaction between humans and machines.This change significantly influences economic security -a socio-economic paradigm that safeguards the economic interests of personnel.The primary objective of this study is to explore the development of personnel management information systems during the economic security transition within the context of Industry 5.0.This involves the modelling of a personnel management information system, which constitutes the main scientific task of the research.The scope of the study extends to the broader personnel management system and the economic security of a unified information system.To accomplish the theoretical and scientific objectives, we employed contemporary methodological approaches for modelling and graphical representation.The results of the study, presented visually, provide a model for information systems for personnel management during the transition of economic security to Industry 5.0.Evidently, the novelty of this study lies in its proposed methodological approach and the delineation of specific processes that facilitate the organization of a personnel management information system amidst the transition of economic security within the context of Industry 5.0.This study's findings contribute to the body of knowledge by providing a comprehensive model for navigating these transitions in the era of Industry 5.0.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.013 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".