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Record W3198823557 · doi:10.1080/23311886.2021.1973196

Revitalising abandoned heritage villages: the case of Tinbak, Qatar

2021· article· en· W3198823557 on OpenAlexaff
M. Salim Ferwati, Sherine El-Menshawy, Maha E.A. Mohamed, Sami Ferwati, Faisal Al Nuami

Bibliographic record

VenueCogent Social Sciences · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsUniversity of Toronto
FundersQatar University
KeywordsTourismSustainabilityCultural heritageSWOT analysisStakeholderEnvironmental planningCultural heritage managementHuman settlementHeritage tourismIndustrial heritageEnvironmental resource managementGeographyBusinessPolitical scienceArchaeologyPublic relationsMarketing

Abstract

fetched live from OpenAlex

As an archaeological heritage, valuable heritage settlements entail preservation to avoid destruction and eventual extinction. Intending to propose a study for revitalising heritage villages, Tinbak is selected as a case study. It is an old abandoned village in Qatar identifiable by its distinct yet straightforward local architecture features. This article applies the concept of sustainable tourism to architectural heritage with consideration to social, cultural, and economic factors. The study employs qualitative research methods, grand and mini-tours, interviews and SWOT analysis with attention to three objectives, 1. Maintain the domestic identity of Tinbak; 2. Shift the value of space from residential to an attractive, sustainable touristic place; and 3. Highlight the connectivity to adjacent communities and open lands as a means of enhancing accessibility and ecotourism. To implement tourism sustainability, the study suggested the guidelines of the albergo diffuso model that promote local culture, stimulate the local economy and considering environmental sustainability. Recommendations suggested protecting and conserving the existing heritage, considering the surrounding rural area as part of revitalising the village, engaging the stakeholder and the citizens in the decision-making, and revitalisation management to ensure the successful transformation of a heritage village from an abandoned place to an operationally sustainable tourist centre.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.203
GPT teacher head0.307
Teacher spread0.103 · 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.

Study designTheoretical or conceptual
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

Citations9
Published2021
Admission routes1
Has abstractyes

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