Climate change impacts on immovable cultural heritage in polar regions: A systematic bibliometric review
Bibliographic record
Abstract
Abstract Over the past decade, research on the impacts of climate change on immovable cultural heritage (ICH) in the polar regions (Arctic and Antarctica) has slowly increased. This article offers a systematic review and synthesis of the publications about climate change impacts on the diverse ICH and climate change adaptation in the polar regions. Gray literature was not included in the study. Arctic countries like Sweden, Finland, Iceland, and Russia, and their associated research organizations, are under‐represented in this literature when compared with the USA, Canada, Denmark, and Norway. More than half of the analyzed literature is published in the last 3 years (2019, 2020, and 2021) with a focus on coastal erosion and ICH degradation (cryospheric hazards). ICH is at risk from biological degradation, coastal erosion, debris flow, and thaw slumping. Nearly half of the studies report on the need for climate change adaptation planning and implementation for ICH. This study shows that advances in research on climate change impacts and adaptation responses are needed to improve decision‐ and policy‐maker capacity to support effective adaptation policies and to contribute to the achievement of SDGs in polar regions. The polar regions' vulnerable landscapes and ICH sites can be used to communicate a larger message about the climate change challenges and adaptation measures. This article is categorized under: Assessing Impacts of Climate Change > Observed Impacts of Climate Change Vulnerability and Adaptation to Climate Change > Learning from Cases and Analogies Climate and Development > Sustainability and Human Well‐Being
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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 | 0.009 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.075 | 0.096 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".