Turismo de festivales en España: evolución, impacto y estudio de caso
Bibliographic record
Abstract
El turismo ha ido evolucionando y ha tenido que adaptarse a la demanda del consumidor, el turismo de festivales ha sido uno de los productos que se ha creado debido a las nuevas exigencias. Este turismo ha ido evolucionando desde la década de los 90 hasta la actualidad. Este turismo de macro eventos favorece sobretodo a la economía de la zona, ya que permite la creación de empleos y beneficios en el sector de la hostelería. En España encontramos festivales que atraen a un gran número de personas, debido a que se conocen a nivel nacional e internacional sobretodo por la promoción que se realiza de ellos. El FIB es uno de ellos, como consecuencia de ser uno de los primeros festivales que se crearon en España y además posee un impacto positivo en el municipio en el cual se realiza.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".