Risk management at heritage sites: A case study of the Petra world heritage site
Bibliographic record
Abstract
The Risk Mapping Project in Petra, collaborative project, started in February 2011 for a period of fifteen months in response to the increasing risks for loss of heritage values at the site and a need for their assessment and proposing responses to reduce their impact. Petra Archaeological Park (PAP), the most significant World Heritage site in Jordan, with its unique landscape, monuments and natural gorges, is a fragile property. Further to its inherent fragile characteristics, Petra is endangered by natural and human-made threats and impacts. Lack of an implemented management plan coupled with no clear property boundaries and an absence of buffer zones as remcommended by the World Heritage Committee, and weak visitor management strategies, result in major gaps in the management of the property and increasing risks to the site. Accordingly, risk assessment and research to better address the challenges of the management of Petra Word Heritage site have been identified as the most appropriate tools for mitigation of risks and protection of the values of the property. This publication examines a systematic approach in order to identify threats, their causes, and understand and access their effects, and proposes ways to choose reponses and mitigation strategies in order to reduce the impact of threats. This publication presents a risk management methodology to be used as a systematic tool for the better management of heritage sites. The methodology developed incorporates similar approaches used by the International Centre for the Study of the Preservation and Restoration of Cultural Property (ICCROM), and the Canadian Conservation Institute (CCI)-Institute for Cultural Heritage of the Netherlands (ICN).
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".