Estrategias de transformación de una economía tradicional excluida a una economía asociativa basado en el ecoturismo como estrategia de desarrollo sustentable para zonas marginadas: Caso zona semiárida de Tamaulipas, México
Bibliographic record
Abstract
The Government of Tamaulipas, Mexico has sought to promote sustainable development in the semi-arid area through the ecological tourism. But since there were cases of success and failure resulting from the implementation of ecotourism, arises the question: what are the successful development strategies on ecotourism taken by the State, the community and investors, which must constitute a system of inter-municipal management relating to ecotourism as a regional development strategy?. Research whose goal was the construction of an ecotourism that transforms a traditional economy excluding an associative economy concerning inter-municipal management system was developed to answer the previous question. Using the systemic archetypes and arguing the five disciplines of learning organizational analyzed structures that make up the process of planning and control of ecotourism, as well as their circles of load and displacement in areas that have set up an ecotourism with results concerning sustainability (Arenal, Manuel Antonio Costa Rica and Niagara Falls, Canada). Determining the degree of organizational learning in the semi-arid area proposed strategies and a system for managing ecotourism inter-municipal so looking for a transformation an associative economy-oriented.
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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 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".