Local Attitudes on Protected Areas: Evidence from Sumava National Park and Sumava Protected Landscape Area
Bibliographic record
Abstract
The present article aims to describe perceptions and awareness of local residents in two categories of the Sumava region protected areas–National Park (NP) and Protected Landscape Area (PLA). The survey explores perceptions of individuals on nature protection, protected area management, tourism and related issues. Differences between these two research areas are also explored. Standardised personal interviews were conducted during the summer season of 2008. The study took place in six municipalities in NP (Borova Lada, Srni, Prasily, Kvilda, Horska Kvilda and Modrava; 183 questionnaires in total) and in three municipalities in PLA (Kasperske Hory, Hojsova Straz and Cachrov; 138 questionnaires in total). According to the results of the study, there were more natives and indigenous residents in NP than PLA. Similarly, local people in NP were working more often in the public sector and less in the private sector and they had more benefits from tourism. Residents in PLA were less informed about Administration activities, more satisfied with topical nature conservation level and against expansion of NP to their place of residence. Also, a significant finding of the study is that residents (especially in PLA) were supportive of some forms of participatory management. They are interested in the advancement of the area, mostly in the form of improvement of tourism-related facilities. They love this region and also call for better communication with NP/PLA Administration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".