Beyond survival : intergenerational climate justice as a conceptual framework for Arctic climate adaptation
Bibliographic record
Abstract
The Arctic is experiencing climate change at nearly four times the global rate, placing Indigenous and local communities under acute pressure to adapt. While adaptation in the region is often framed in terms of resilience and survival, such approaches risk overlooking the ethical and temporal dimensions of climate governance. This article argues that intergenerational climate justice provides a critical conceptual framework for rethinking Arctic adaptation. Drawing literature on climate adaptation and justice, the paper outlines four key pillars: continuity, inclusivity, foresight, and responsibility, that together offer a pathway “beyond survival” toward justice-oriented futures. Case examples from across the Arctic illustrate how these principles are already emerging in practice: Sámi youth movements resisting extractive land uses in Fennoscandia, Inuit advocacy linking adaptation to food security in Canada, community relocation efforts in Alaska, and youth-led litigation addressing state responsibility in Norway. These developments highlight the ways in which adaptation is inherently intergenerational, shaping not only present conditions but also the cultural and ecological legacies inherited by future generations. The article concludes that embedding intergenerational justice into adaptation strategies is essential for the Arctic and offers broader lessons for global climate governance, where short-term responses must be balanced with long-term responsibilities.
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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 | 0.008 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.048 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".