Bibliographic record
Abstract
In modern tourism, the concept of big and mass tourism has been abandoned, and the support has been given to responsible development based on the selected types of tourism.The existing mass and uniform types of tourism are being refined by new and higher quality contents; on the other hand, new types of tourism are also being developed which, thanks to their originality and diversity, enrich its content.In that context, culture has a direct impact on tourism and tourism increasingly affects culture, which has become an important motive for tourist travel.While some 30 years or so years ago cultural tourism implied heritage tourism, that is, visits to cultural and historical monuments, museums and galleries, some 10 years ago that phenomenon underwent its transformation, so that today the same term also implies different cultural and entertainment events and almost all manifestations of living and working cultures.Today, cultural tourism includes tourist travel during which tourists are active participants in the cultural life of the social community they visit, and popular culture represents the part of non-material cultural heritage which forms a new, although often neglected, way of the tourism product diversification.It is our aim to review the general trends in cultural tourism today as well as reveal the realities of the Croatian cultural-tourism product and establish the level of its development within contemporary Croatian tourism.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".