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Record W3197584193 · doi:10.18280/ijsdp.160401

Analysing the Public Administration and Decision-Makers Perceptions Regarding the Potential of Rural Tourism Development in the Azores Region

2021· article· en· W3197584193 on OpenAlexvenueno aff
Rui Alexandre Castanho, Gualter Couto, Pedro Pimentel, Célia Barreto Carvalho, Áurea Sousa, Maria da Graça Batista

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsTourismAdministration (probate law)Environmental planningPerceptionRegional scienceRural developmentGeographyBusinessPolitical scienceEnvironmental resource managementPsychologyEnvironmental science

Abstract

fetched live from OpenAlex

Considering that tourism is one of the drivers of the development of peripheral territories, it seems essential to understand the main regional actors' opinions and perceptions to design more coherent and successful sustainable development regional plans. In this regard, the present study intends to assess the Public Administration and Decision-Makers perceptions Regarding the Potential of Rural Tourism Development in the Azores. Contextually, through an exploratory methodology, it was possible to assess the Azores Public Administration and Decision-Makers perceptions. Therefore, it was possible to understand that the majority believe that rural tourism has increased in the Azores Region's last decade (90.2%). Regional development has been positive and has positively impacted the local population (97.6%). Besides, the decision-makers and public administration assign greater importance to the "Protection and conservation of Nature" and "Greater commitment and political transparency" as the most critical factors for the success of rural tourism in the Region. The study also identifies the main benefits of this type of tourism for local communities: job creation, Strengthening the local economy, countering local desertification, and developing trade, services, and activities. Therefore, the design of future regional plans that aim at sustainable development must definitely consider the factors identified concerning rural tourism.

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.446
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.324
Teacher spread0.300 · 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 teacher head, 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

Citations22
Published2021
Admission routes1
Has abstractyes

Explore more

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