Modeling Effective Interaction Between Society and Public Administration for Sustainable Development Policy
Bibliographic record
Abstract
The main purpose of the article is to determine the ways of interaction between society and the system of public administration on sustainable development policy. For this, the main scientific task is to model the process of interaction between society and the public administration system regarding sustainable development policy. The object of the study is the policy of sustainable development of a particular region. To achieve the goal, the methodology of the article involves the use of a modern modeling method through the technology of graphical structural analysis. As a result, we have obtained a hierarchical data model with the corresponding processes for achieving effective interaction between society and the public administration system for sustainable development policy. The novelty of the results obtained in the article is manifested through the proposed methodology of graphical structural analysis in the context of increasing the policy of sustainable development. The study has a limitation in the form of a narrowed view of modeling the interaction of society with the public administration system regarding sustainable development policy, namely, only for the selected region. Prospects for further research are aimed at expanding the methodology through modeling more elements of the interaction of society with the public administration system regarding sustainable development policy. We have chosen the Cotswolds (England) region, which is chosen due to its strong system of public administration and the focus on cooperation in the framework of sustainable development. The limitations presented in the article influence the findings by the fact that the results are targeted at individualism.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".