Revitalising abandoned heritage villages: the case of Tinbak, Qatar
Bibliographic record
Abstract
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.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".