TOWARDS SUSTAINABLE HERITAGE CONSERVATION IN EGYPT: A DETAILED ANALYSIS FOR IDENTIFYING THE VALUES USED IN SELECTING HERITAGE BUILDINGS
Bibliographic record
Abstract
Listing heritage buildings in a certain country is the first step towards building conservation and sustainability.Thus, national governments, agencies, or organizations are responsible for deciding whether a building is of special value that should be listed.Different building conservation systems all over the world aim to preserve their heritage by identifying values based on the global principles agreed upon in all charters and treaties.Value concept passed through a long evolution of human thought including historical, artistic, social, political, educational, cultural, and many others.However, such various dimensions of values have become beyond the discussion and analysis of heritage conservation projects.This research seeks to identify and collect all values for selecting heritage buildings to facilitate their registration and management.Therefore, the study focuses on reviewing the existing criteria for listing heritage buildings in five countries: Canada, United States, United Kingdom, Australia, and the European Union.According to the results of the content analysis, by summing up all criteria needed for listing heritage buildings, a detailed analytical study for values and their indicators is conducted to improve and facilitate the listing management system in Egypt.Furthermore, the result shows the values and indicators that need to be added in the assessment criteria of Egyptian national law.This can raise the awareness and significance of various heritage buildings preventing their neglect and demolition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".