Public Administration of Planning for the Sustainable Development of the Region in the Context of Total Digitalization
Bibliographic record
Abstract
The main purpose of the article is to form a mechanism for public administration of the planning system for the sustainable development of the region in the context of digitalization. To achieve the goals set, the method of graphical construction of the functional mechanism was used. The use of this technique made it possible to depict in detail the process of achieving the final goal. In addition, a significant advantage of this model is that the modeling system takes into account the functional relationships of the stages and the main elements of the system necessary to achieve the ultimate goal. The relevance of the study is given by the factor of active discussion of the public administration system and consideration of its significance for the sustainable development of the region. Based on the results of the study, the main functional mechanism of state management of the planning system for the sustainable development of the region in the context of digitalization is presented. With the help of the constructed mechanism of state management of the planning system for the sustainable development of the region, public administration authorities will be able to better plan their activities and increase the efficiency and speed of digitalization processes. The study has limitations and whether they are related to the narrowing of the analysis by focusing solely on the system of public administration in the region. Further research should be devoted to the problems of the direct implementation of this mechanism in the planning system for the sustainable development of the region.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".