Fostering sustainable leisure activities: a behavioural insight into eco-friendly intentions in Mount Damavand
Bibliographic record
Abstract
Mount Damavand, the highest point in the Middle East and one of the most popular peaks in the region, is experiencing environmental degradation due to hikers’ activities, exacerbated by inadequate regulations and infrastructure to manage visitor volume and behaviour. This study delved into the pro-environmental behavioural intentions of hikers within the Mount Damavand National Park. Employing partial least square structural equation modeling (PLS-SEM), we examined a proposed framework extending the theory of planned behaviour by including the value-belief-norm theory and a formative approach to study constraints to pro-environmental behaviours of hikers. We analyzed a sample of 393 hikers. The findings underscored the effectiveness of amalgamating these theoretical frameworks and elucidated 46% of the variance in pro-environmental behavioural intention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".