Visitor outcomes from dark sky tourism: a case study of the Jasper Dark Sky Festival
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dark sky tourism is a growing, but under-studied sector of ecotourism. While some research has examined the economic impacts, regional sustainability, and management of dark sky tourism, researchers know little about tourist experiences and outcomes. This study seeks to determine visitor outcomes (satisfaction, learning, attitudes, and behavior changes) among participants at the Jasper Dark Sky Festival in Alberta, Canada. Visitors were middle-aged, balanced between genders, traveled an average of 430 km, and were primarily urban-based. Most were first-time visitors, were present 2 or more days, and attended over 5 festival events. Respondents reported high satisfaction levels, due to the low cost and diversity of events, and welcoming nature of the community, presenters, and volunteers. Respondents reported many areas of learning, particularly about the night sky and night animals. Respondents had very positive attitudes about protecting dark skies, but only 42% planned to change any behaviors to protect dark skies. Study results will help festival organizers design dark sky tourism events to optimize visitor outcomes. In particular, festival organizers can address some barriers to behavioral change, such as stressing the value of dark skies and providing information about how to reduce light pollution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it