Creative Tourism in Smaller Communities: Place, Culture, and Local Representation
Bibliographic record
Abstract
As more people travel the world than ever before, smaller communities have a unique opportunity to develop creative, culturally sustainable tourist industries that provide unparalleled experiences for visitors. Tourists are travelling the world in greater numbers than ever before, seeking immersive cultural experiences. This massive rise of tourism has raised issues of social and cultural sustainability in the world’s global cities. At the same time, smaller cities and rural communities struggling with increasing urbanization and the loss of traditional industries could benefit from increased tourism. Smaller cities and communities are uniquely well-suited to hosting tourists seeking authentic connection with local cultures. Locally led, collaborative efforts to build creative tourism industries have the possibility to reinvigorate struggling communities. Creative tourism offers the opportunity to build socially and culturally sustainable channels for growth that benefit locals and visitors alike. Creative Tourism in Smaller Communities examines the processes, policies, and methodologies of creative tourism, paying special attention to the ways creative and place-based tourism can aid sustainable cultural development. With topics ranging from placemaking through food to the cultural impacts of cruise travel, and from catalyzing creative tourism to creating resiliency, this collection offers a wide range of theoretical and practical perspectives from a variety of experts. Creative Tourism in Smaller Communities offers a bold vision for the future of tourism worldwide.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".