Risk management at heritage sites: A case study of the Petra world heritage site
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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).
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it