Rural landscape and preservation of natural environment: Opinions and attitudes of examinees resident within Krka river basin
Bibliographic record
Abstract
This paper includes the presentations of development perspectives of the villages along the right bank of the Krka river that are within, or on the edge of the Krka National park and the results of empirical research of the opinions and attitudes of the local population regarding the preservation and protection of the environment in this area. Using the survey method, we examined the opinions of the adult population of Krka river basin in the rural area of Skradin hinterland. The questions focused on a number of issues regarding preservation and/or threat to the environment. The research is a part of the project "Titius: Krka river basin - heritage and socio-cultural development", which is conducted by the Department of Sociology, University of Split. The results of the survey show that great majority of respondents think that the environment in their region is entirely or mostly preserved, and in the same time more than half of respondents agrees with the statement that the soil is contaminated with artificial additives and that the agricultural products are increasingly less natural, as a result of the technologies used in farming. Also, almost three quarters of the respondents consider that the rivers and water are not polluted, and one quarter argues that the illegal dumps, especially of plastic materials and bulky waste spread everywhere, and that the cars and the local industry have polluted the air in their living area. Attitudes and opinions are discussed in relation to socio-demographic characteristics of respondents and their level of education.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".