Willingness to Pay in Kinabalu Park, Malasia: A Portrayal of the Meanings of Kinabalu
Bibliographic record
Abstract
The central question addressed in this paper is whether tourists visiting a protected area are willing to pay more and what are the reasons behind such motives, so as to enhance tourism revenue in protected areas. Studies have concluded that most parks are charging fees far below what visitors are willing to pay, and thus suggest that parks charges for entrance, activities, and facilities should be increased accordingly to conform to the user-pay scheme. It has been widely recognized that reasons for willingness to pay more differ from one individual or group from another, and that the most noticeable factors are related to the various perceptions held by an individual/group of what a protected area should be and what it offers, as well as the roles it plays. These perceptions are captured within the nexus of visitor backgrounds. For the purposes of this paper, the authors focus on foreign visitors. How pre-existing perceptions of a protected area “is supposed to be” influence willingness to pay among for...
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".