The effects of forest industry impacts upon tourist perceptions and overall satisfaction
Bibliographic record
Abstract
Due to the growth of nature-based tourism during in recent decades, the value of forested areas for the tourism industry has been increasing. This is largely due to the aesthetic values that are often associated with forests. However, forests are also highly valued for timber production, an activity that can seriously compromise the visual quality of forested landscapes. Therefore, this article examines the effect that forest industry impacts have upon tourist perceptions and overall satisfaction in destinations that promote natural landscapes to attract visitors. To help understand this issue, tourists were surveyed at natural attractions in Vancouver Island, Canada and Tasmania, Australia. Results suggest that certain forest industry impacts do have the potential to negatively impact upon tourist perceptions in the two destinations included for this analysis. However, there appear to be a number of additional elements that are also important for shaping the perceptions of tourists, as overall satisfaction ratings were shown to be quite high for both Vancouver Island and Tasmania.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".