Resilience, human agency and climate change adaptation strategies in the Arctic
Bibliographic record
Abstract
In the Arctic, indigenous peoples, researchers and governments are working to develop climate change adaptation strategies due to the rapid changes in sea ice extent, weather conditions and in the ecosystem as such. These strategies are often based on specific perceptions of vulnerability and work with a number of barriers for resilience. The objective of the article is first to address the position of institutional barriers in the studies and strategies. Second the article analyses the role human agency is ascribed in proposed strategies and projects in Nunavut and Greenland. With a focus on institutions and human agency the question is not only ‘how do people manage to adapt?' but moreover ‘what constrains people in pursuing a given adaptation strategy?' The article introduces the concept of double agency which stresses two different aspects of human agency that can be used to understand the political processes taking place in the Arctic: one aspect emphasises stakeholder participation and integration while the other aspect emphasises rightholder possibilites and self-determination. The focus is thus on how adaptation strategies relate to political and legal processes at different scales and the implications for resilience.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".