Influjo de las alertas de viaje en un contexto de inseguridad internacional: el caso de Mazatlán, Sinaloa (México)
Bibliographic record
Abstract
espanolA partir del siglo XXI la seguridad se convirtio en uno de los indicadores mas influyentes al momento de planear un viaje. Desde entonces los diferentes estados nacionales han establecido politicas y mecanismos para informar y advertir a sus ciudadanos sobre el peligro o riesgo que existe al viajar a otros sitios alrededor del mundo, siendo el asesinato el rubro con mayor peso al momento de emitir dichos avisos oficiales. El presente articulo evalua el efecto que produce una alerta de viaje entre el flujo de visitantes norteamericanos y canadienses a un destino turistico mexicano a traves de diferentes indicadores turisticos y el numero de homicidios registrados entre el ano 2006 y 2016, a traves de tecnicas econometricas como el metodo de regresion lineal multiple. Entre los resultados es posible demostrar la relacion que tienen los homicidios con la ocupacion hotelera y el porcentaje de ocupacion de turistas nacionales como extranjeros en el puerto turistico de Mazatlan, Mexico. Asimismo la evidencia estadistica establece que este tipo de delitos influyen en el flujo de visitantes internacionales al destino de manera moderada, pero no en su permanencia. EnglishInfluence of Travel Alerts in a Context of International Insecurity. The Case of Mazatlan, Sinaloa (Mexico). From the 21st century, security became one of the most influential indicators when planning a trip. Since then the different national states have established policies and mechanisms to inform and warn their citizens about the danger or risk that exists when traveling to other places around the world, with murder being the item with the greatest weight when issuing such official notices. This article evaluates the effect produced by a travel alert between the flow of North American and Canadian visitors to a Mexican tourist destination through different tourism indicators and the number of homicides registered between 2006 and 2016, through econometric techniques such as the multiple linear regression method. Among the results it is possible to demonstrate the relationship between homicides with hotel occupancy and the percentage of occupancy of domestic and foreign tourists in the tourist port of Mazatlan, Mexico, as well as statistical evidence that this type of crime influences the flow of international visitors to the destination in a moderate way, but not in their permanence.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".