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.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".