STRATEGIC ASPECTS OF DIVERSIFICATION AND MODERNIZATION IN THE ECONOMY OF SINGLE-INDUSTRY SETTLEMENTS
Bibliographic record
Abstract
The current research features approaches to solving the problems associated with a decline in the development of old industrial sectors in single-industry towns (monocities, or monocommunities). The target of the study is to show the necessity of strategic approach and interaction of all management levels. Particular attention is paid to resource-dependent communities. Enterprises of mineral resources sector have limits of effective development, associated with gradual depletion of their resource base. Diversification and modernization of the economy of resource-dependent communities are logically linked to a timely achieving of strategic objectives to ensure their long-term sustainable development. Strategic aspects are also important for development planning in the sphere of new raw material deposits. A comprehensive analysis should help avoid the risks of creating new monocommunities with a poor prospect of long-term development. The article includes an analysis of international experience of Germany, Canada, and China. It is shown that a progress in solving the problems of company towns heavily depends on a strategic partnership between the federal, the regional, and the municipal governments, as well as on their collaboration with business. A conclusion is made that a uniform strategy for the development of various single-industry towns does not exist. The choice of the way of the development for each particular monotown is determined by its socio-economic characteristics. Among those, remoteness or proximity to large urban agglomerations, industry affiliation and prospects for the development of the cityforming enterprise, opportunities for economic diversification, investment potential and opportunities for attracting investors are of paramount importance. The process of positive changes, as a rule, is slow and complicated. Thence, it is important to justify the purpose and ways to achieve it. As a rule, extrapolation methods do not work in this case
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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 | 0.001 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".