Ecological Aspect of the Analysis of a Project for Economic Development of the Kurshskaya Kosa (Curonian Spit) National Park as a Specially Protected Natural Territory
Bibliographic record
Abstract
At the present time, ecological economics is one of the most widely used approaches to the analysis of economic development projects whenever they have bearing on specific eco-systems. This article illustrates possibilities of successfully applying the concepts of ecological economics to the analysis of projects aimed at the economic development of specially protected territories on the example of the economic development of the Kurshskaya Kosa (Curonian Spit) National Park. From the viewpoint of the ecological-and-economic analysis of the Environment-Society-Economy system, the article investigates the economic, ecological, social aspects of the prospective development of the Kurshskaya Kosa (Curonian Spit) national park; the index of degradation is used as a non-financial integral index of the assessment of the prevailing condition of the national park. Based on conducted research, conclusions reached to the effect that it is necessary to render more precise a methodology for determining the recreational capacity of the national park as a specially protected national territory; evidence is provided for the need to reduce a recreational load on the national park. From the viewpoint of the concepts of ecological economics, the article provides rationale for a system of ecological restrictions and indices to be used in designing and building tourist- and recreation facilities at specially protected natural territories. In the writing of this article, the authors use comparative analysis methods, induction and synthesis methods and mathematical methods. The provisions and conclusions of this paper have a direct bearing on the formation of economic policies for the development of the national park as a specially protected territory and, in the final analysis, on the social status of the population living and working within the territory of the national park.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".