The CARRA project: Developing tools to help heritage managers identify and respond to coastal hazard impacts on archaeological resources
Bibliographic record
Abstract
Coastal archaeological sites in Newfoundland and Labrador are currently under considerable threat, with important knowledge of the province's history and prehistory potentially lost to erosion. Climate change will exacerbate existing coastal hazards, thus causing even greater loss of archaeological resources in the future. Action is needed now to protect or retrieve the information from significant sites under threat in coastal areas before they are completely eroded. In responding, cultural resource managers face potentially tough questions about which sites are at risk, how to prioritize at-risk sites for action, and what management option is most appropriate. A 2011 study by Westley et al. estimated that one-fifth of the coastal archaeological sites in three study regions of Newfoundland were highly vulnerable to the impacts of relative sea-level rise (SLR), storm surges or coastal erosion over the next 15-50 years. The Coastal Archaeological Resources Risk Assessment (CARRA) project aims refine the site vulnerability assessment approach and inform management decisions about at-risk sites. This includes employing high resolution coastal topography (e.g. LiDAR), revised SLR projections, updated coastal erosion estimates and resurveyed site positions in our improved vulnerability classification. Once at-risk sites have been identified, prioritizing action at these sites is especially difficult. A review of the published literature revealed few examples of applied processes and those identified rely heavily on the quantification and ranking of risk factors with less emphasis on the nature and rarity of the archaeological resource. The CARRA project is reviewing current practices in at-risk site prioritization with the goal to create best practice scenarios for one of our Newfoundland study areas. This process will involve detailed hazard assessment of two at-risk sites, including coastal erosion and shoreline retreat studies, as well as an impact assessment of known archaeology resources at each site under future hazard scenarios. The final step in the management of at-risk archaeological sites is the design and implementation of an action plan. The CARRA project aims to inform this step through a review of current case studies and management actions at threatened sites across Canada. Two case studies from Newfoundland are briefly introduced to illustrate the types of local actions taken to mitigate erosion at archaeological sites. These case studies will be reviewed in detail with the intention to share adaptation strategies as part of a new community of practice for heritage managers responsible for coastal archaeology resources in Canada.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".