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Record W2072490136 · doi:10.2495/sdp-v10-n1-1-19

Accelerating cultural heritage tourism in San Antonio: a community-based tourism development proposal for the missions historic district

2015· article· en· W2072490136 on OpenAlexvenueno aff
S. Doganer, William Dupont

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
FundersNational Park ServiceUniversity of Texas at San Antonio
KeywordsProsperityTourismCultural heritageIndustrial heritageCultural heritage managementTourism geographyCultural tourismSustainabilityLocal communityHeritage tourismSustainable developmentBusinessPolitical scienceEconomyEconomicsLaw

Abstract

fetched live from OpenAlex

Cultural heritage tourism is a proven economic stimulus that creates jobs and direct economic benefits to locals.Heritage zones promote conservation of historic resources and can incubate small businesses, revitalize commercial districts, generate local jobs and foster positive change in a community.The social benefits are many, yet long-term retention of the benefits requires deliberate planning.The prosperity brought by the tourists tends to destroy the experiences they seek.Heritage tourists seek experiences of authentic cultural heritage.Yet, the economic prosperity of tourism can swiftly alter a region.Business and real estate development pressures increase as the tourist market expands, bringing changes that occlude and displace the local heritage.This paper posits that attention to cultural sustainability can mitigate negative impacts and correlate to a robust heritage tourism economy.Sustainable development practices can support cultural heritage tourism in a manner that sustains the local culture.The San Antonio Missions and potential development in South San Antonio are reviewed here as an economic development tool designed to attract visitors to an area based on the unique aspects of the locality's history, landscape and culture.The heritage tourism market needs cultural heritage in order to grow and retain the economic prosperity over time.This research investigates and analyzes the potential of the San Antonio Missions Historic District toward community-based cultural heritage tourism.The connections of Missions to the river will feature historic and artistic interpretations of the story of the missions and highlight their social and cultural importance to the area.This will reinforce the importance of the river to the missions and encourage visitors to circulate between the Mission Reach and the river.Accelerating tourism in Missions Historic District will be a considerable economic and social benefit through the workforce, income and infrastructure developments.This research provides a legacy of positive development within the Missions Historic District, especially as San Antonio moves toward World Heritage designation.World Heritage designation brings international attention and increased tourism with both positive and negative impacts.Cultural heritage tourism can bring many benefits to a local economy but it can also disrupt the quality of life of the local inhabitants.This research also investigates how to prevent gentrification and the loss of authenticity while tourism in the district accelerates.This paper also promotes cultural and environmental sustainability at the local or neighborhood level, and highlights the potential benefits for small business owners to connect to the growing heritage tourism economy of the San Antonio Missions Historic District.Prosperity for residents of the district is a viable path to sustaining the community's cultural heritage, identity and authenticity.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0130.001

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 head0.085
GPT teacher head0.358
Teacher spread0.273 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2015
Admission routes1
Has abstractyes

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