The cultural legacy of the frontier lands of Vinalopó (Alicante, Spain) and their tourist use – impossible mission?
Bibliographic record
Abstract
“Frontier tourism” or tourisme de partage is a genuine typology of tourism which has these four features: space (geographic), time (historic), experience (motivations and behaviours) and sharing cultural heritage (material or immaterial). The border lands of Alto Vinalopó (Alicante-Spain) have a paradoxical and dual element in the sense that they operate as a territory with common customs and traditions which share many similarities with other territories, but at the same time they show a number of contrasts and peculiarities. Reorganized now as potential tourist attractions, these deep-rooted ethnographic displays are becoming consumable products, which are struggling to find a differential position in the leisure business. This article is aimed at illustrating this process, analysing its sociocultural, economic and promotional variables by considering a particular event: the Moors and Christians festival in Villena. These ancient celebrations convey their own values and signs of identity which have also served to stimulate and diversify the local economy. Besides, after being officially declared in 2015 a national tourist attraction, with the “4th September, All Mad” campaign, this festival has generated challenges, uncertainties and opportunities for tourist development which will demand the right creative strategies and economic management to succeed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".