Influence of Closed-Loop Technologies on Local Development of Communities and Formation of Their Social and Economic Security
Bibliographic record
Abstract
Regional development in Ukraine is an important component of state policy.This is due to the fact that in the conditions of social and economic security, each community will be provided with security of the country as a whole.This study is topical in the role of community development for the modern economy of Ukraine.In the article describes how technologies of a closed-loop in the territory of regions help to achieve the highest level of social and economic security.The purpose of the work is to image this influence.The main method of writing the article was the analysis.In the article the author showed that the impact on the development of the region from the introduction of the concept of circular economy on its territory will be generally positive.This is justified by the reduction of dependence of the region on resource prices and other external factors, the reduction of the price of products in the long term, the lower pressure on ecology, creation of new jobs and some other advantages.However, the introduction of this concept of development can create some problems, especially at the initial stage.They are connected with financing of processing technologies, because of which local communities will need considerable support of the state.The article will be useful for studying ideas of sustainable development and helps other authors in writing theirworks;also, it can be useful for analysis of socio-economic situation in regions of Ukraine, etc.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".