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Record W3199232682 · doi:10.47197/retos.v1i40.82749

Análisis del perfil demográfico y consumo turístico en eventos deportivos en la ciudad de Quito. Caso de estudio: Roger Federer (Analysis of the demographic profile and tourist consumption in sporting events in the city of Quito. Case of study: Roger Fed

2020· article· es· W3199232682 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRetos · 2020
Typearticle
Languagees
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsImpact
Fundersnot available
KeywordsGeographyHumanitiesTourismArt

Abstract

fetched live from OpenAlex

El desarrollo del turismo en las ciudades plantea dos aspectos de importancia. En primer lugar, es su objetivo que el turismo impacte en el desarrollo local y, en segundo lugar, que la oferta turística se diversifique y se complemente. En esta coyuntura, la ciudad de Quito apostó por el apoyo a un evento deportivo, de gran envergadura, para el mes de noviembre del 2019. De esta propuesta surgió la necesidad de medir el impacto del evento deportivo en la ciudad y al mismo tiempo identificar la demanda real de turistas nacionales e internacionales. Para ello se aplicó un cuestionario con 23 ítems que fueron agrupados en 2 grupos de factores: la determinación del perfil del consumidor y el consumo turístico realizado. Posteriormente se obtuvieron datos de Quito Turismo sobre el media value del evento, con el cual se estructuró una base de datos para una interpretación integral. Los resultados obtenidos fortalecen la estrategia para que Quito albergue varios eventos de importancia, en diversos aspectos, a más de lo deportivo. La derrama económica en los negocios locales fue significativa y se registró un impacto importante en el posicionamiento de la ciudad como destino turístico. Abstract. The development of urban tourism raises two important aspects. In the first place, tourism must have an impact on local development and, secondly, that the tourism offer should be diversified and complemented. At this juncture, the city of Quito opted to support a large-scale sporting event for the month of November 2019. From this proposal arose the need to measure the impact of the sporting event in the city and at the same time identify the real demand of national and international tourists. For this, surveys were conducted with 23 items that were grouped into 2 groups of factors: the determination of the consumer profile and the tourist economic consumption. Afterwards, data was obtained from Quito Tourism on the average media value of the event, with which a database was structured for a comprehensive interpretation. The results obtained strengthen the strategy for Quito to host several important events, in various aspects, in addition to sports. The economic impact on local businesses was significant and there was an important impact on the positioning of the city as a tourist destination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.335
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it