Sustainability in architectural heritage: review of policies and practices
Bibliographic record
Abstract
Abstract If sustainable development goals are to be achieved, it is necessary to consider refurbishment of architectural heritage buildings as well! As just 1% of buildings in the European Union have been built since 2006, it is essential to turn towards refurbishment of existing buildings if goals of sustainable development are to be achieved. Therefore, this article explores the ways in which sustainable development in construction is encouraged and achieved, especially concentrating on architectural heritage buildings. The idea of sustainable development revolves solely around carbon emissions, and therefore, historic buildings in Europe face the key issue of sustainability. Recently, there has been an increasing interest in reusing existing buildings through refurbishment and adaptive reuse where possible, as building reuse should offer environmental savings over demolition and new construction. In addition, despite popular belief, older buildings are capable of adapting to the new energy efficiency norms. This study explores the possibilities of encouraging complete refurbishment (including both sustainable renovation and strengthening) of historical buildings by exploring incentives used in Europe, the USA, Canada and New Zealand. Based on the literature review and best practices, the article concludes with recommendations on how to increase the positive investment flow of private capital into architectural heritage buildings, thus ensuring both preservation of heritage and achievement of sustainable development goals. The findings help both the user of the initiative on gaining insight into the intervention process that can be expected, as well as the local and regional governments interested in boosting adaptive reuse and refurbishment of existing buildings in order to achieve sustainable development goals.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.017 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".