Traditional Cultural Heritage vs. Film Sceneries: Evaluating the Degree of Sustainability of Cultural Landscapes
Bibliographic record
Abstract
Cultural tourism is a good way to promote and, consequently, safeguard the cultural heritage of sites. Film tourism is an increasingly demanded form of cultural tourism more focused on the fictional rather than on the authenticity of sites, depriving them from their true identity. This article is proposing a system of indicators of sustainable development in order to evaluate and guarantee long-term sustainability in those sites identified with traditional cultural heritage and where films have been shot. The Historic Centre of Peñíscola, which was declared a Historic-Artistic Site in 1972 and has become film scenery in numerous occasions, has been chosen to be evaluated. The union of a series of film sceneries obtained from the cinema productions that best match the local heritage, through the latter has resulted in a final cultural landscape where the degree of conciliation between them is high. Therefore, the welfare of the host society is in balance with the tourist demands, which makes the Historic Centre of Peñíscola an accurate study case that can contribute to improve a methodology we aim to extrapolate to other tourist destinations threatened by a new uncontrolled mass of tourist.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".