Adaptation Actions for a Changing Arctic: Perspectives from the Bering-Chukchi-Beaufort Region
Bibliographic record
Abstract
In May 2013, the Arctic Council requested the Arctic Monitoring and Assessment Programme (AMAP) to “produce information to assist local decision-makers and stakeholders in three pilot regions in developing adaptation tools and strategies to better deal with climate change and other pertinent environmental stressors” (AMAP, 2017). Adaptation Actions for a Changing Arctic (AACA) is the response to that request: an assessment of climate and integrated social and environmental frameworks or models that can inform adaptation actions in the face of Arctic change. Three Arctic regions were chosen by AMAP for pilot assessments to be conducted simultaneously. This report is an assessment for the Bering-Chukchi-Beaufort (BCB) region. It focuses on the challenges that residents have experienced and the adaptations they have implemented in response to the rapid changes of recent decades – in climate, landscape, wildlife, and social, economic, and health systems. It also looks to the future and analyzes the strengths and deficiencies in societies’ and individuals’ abilities to adapt, so that decision-makers may better understand where assistance is needed or where alternatives must be developed.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".