Eurocentric cultural theme parks in Japan: domestic tourists’ perspectives on place branding
Bibliographic record
Abstract
During the Bubble Economy era, cultural theme parks were constructed in rural Japan for economic rejuvenation. These cultural theme parks or gaikoku mura (foreign villages) embrace foreign cultures and landscapes rather than rollercoasters. They offer Japanese tourists the foreign travel experience adapted and modified for the Japanese market. Set within place-based branding, imaginaries, and authenticity, this paper compares the Eurocentric theme parks of Huis Ten Bosch in Nagasaki and Yufuin Floral Village in Oita. Opening in 1992, Huis Ten Bosch is a large-scale cultural theme park based on Nagasaki’s historical connection to the Netherlands. Recreating Dutch cities and landscapes, it offers hotels, restaurants, shops, and attractions. Within the hot springs area of Yufuin, the Floral Village opened in 2012, modelled after The Cotswolds, UK. Houses with storybook architecture contain souvenir shops and tea rooms featuring characters from British literature and Studio Ghibli anime. Based on site visits, photographic documentation, and qualitative sentiment analysis of comments written by visitors on TripAdvisor, the paper investigates the perceptions of Japanese tourists. They are positive about Huis Ten Bosch with developers having successfully created and branded a Dutch environment, while mixed messages at Yufuin demonstrate the importance of product-market match for these ‘exotic’ attractions.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 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 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".