Cultural heritage and risk assessments: Gaps, challenges, and future research directions for the inclusion of heritage within climate change adaptation and disaster management
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
Abstract Cultural heritage shapes our identity, delivers capacities, and exposes vulnerabilities, yet cultural heritage value and vulnerability are largely missing from conventional risk assessments. Risk assessments are a fundamental first step in identifying effective mechanisms for Climate Change Adaptation (CCA) and disaster management. However, by ignoring the influence of heritage, decision makers are limiting their understanding of risk and therefore opportunities vital for building and maintaining local resilience. We present findings from a synthesis of peer‐reviewed literature from the last 15 years on cultural heritage risk assessment for primarily CCA but with wider implications for disaster management. We identify a significant lack of research examining intangible aspects of heritage and their influence on risk and resilience. Across the literature, risk assessments focus largely on exposure in isolation from vulnerability or adaptive capacity and where vulnerability is included there is no consistent definition or criterion. We highlight that the most frequently used methods have minimal engagement with local community values, experience, and knowledge relating to heritage practice and customs. Community engagement is most often associated with ‘professional experts’ rather than members of a local community. Furthermore, the Global South is severely under‐represented with a research bias towards Europe and North America. We recommend an agile approach to future assessments with the adjustment of risk tool research and development to include participatory approaches. Future climate risk frameworks must incorporate community‐scale values to understand the role of cultural heritage in relation to adaptive capacity, vulnerability, and resilience.
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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 | 0.002 | 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 | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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