Bibliographic record
Abstract
The article explores the concept of inclusive development of regions, emphasizing the study of the formation and maintenance of a stable level of public health in the scientific literature. For bibliographic analysis, complex scientometric databases Scopus and Dimensions were used to analyze a set of publications formed according to specific criteria using the software tool VOSviewer. The visualization method was used to visualize the obtained results. The search in scientometric databases was carried out by the criterion of the title of the publication, the content of its annotation and keywords. The analysis showed that the main research clusters form groups of scientists' publications from the United States, Great Britain, Australia, and Canada. The small number of publications, but their growth dynamics and the increasing number of citations (according to Google Scholar) indicate a lack of study of inclusive growth in the region in the public health management system and the prospects for its exploration by scientists. According to the analysis, the interest of scientists in solving the problem of public health in ensuring regional development increased in 2020-2021. Much of the publications relate to such areas of knowledge as business, management and accounting. The main areas of research on public health in the development of the regions include the provision of medical services, the health care system, social determinants of health, and the population's state of health. Scientific clusters are gradually being formed around these keywords. The obtained results of the bibliographic analysis form the basis for a better understanding of public health issues, the search for gaps, the solution of which should be worked on in further research. Particular attention is paid to the issue of the COVID-19 pandemic as a crisis-forming factor that hinders the movement of regional development in a promising direction and ensuring the resilience of the system. It is substantiated that the health factor is essential in forming a robust human potential of the country and the growth of labor productivity.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".