Correlation between Creative Tourism and Agrotourism Services Experiences: An Empirical Research in the Mexican Rural Tourism Environment
Bibliographic record
Abstract
There is an immediate need to promote rural areas, where Mexico’s highest poverty is concentrated, but the most potential exists for future development. The preferences of the new modern tourist are based mainly on living experiences rather than just sights and souvenirs. The creative experience as the basis of Creative Tourism can be adopted by agrotourism, a type of Rural Tourism, that consist of tourist activities which are based on experiences that natives in the rural area experience on a daily basis. Thirty tourists from 18 to 23 years of age participated in agrotourism activities such as ointment workshops, food workshops, pulque (an alcoholic beverage made from the fermented sap of the maguey- agaveplant) preparation workshops, embroidery workshops, farming workshops, and a guided trip to the ecological reserve. With the use of narratives, experience maps, and audiovisual materials, the results show that the essence of Creative Tourism was understood as active participation and creativity. Many of the participants expressed novelty as a written and graphic expression of creative tourism which enabled them to have a better overall experience. This finding suggests that agrotourism should include different aspects of creative tourism as part of a “creative experience” for those in charge of the tourism industry in Mexico.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".