Bibliographic record
Abstract
Under climate change, the nature of sacrifice is asymmetrical. This is particularly true for the Arctic as decision makers balance diverse risks and divergent interpretations of science concerning Arctic development. The Arctic’s most prized attributes – its apparent remoteness, wildness, and vastness – lead to assessments that the region is capable of absorbing substantial environmental loss and damage. Indeed, in the modern era, the Arctic has been ripe for sacrifice: for instance, between 1955 and 1990, the Soviet Union detonated 88 atmospheric and three underwater nuclear weapons as tests in the Novaya Zemlya archipelago (latitude 75°10′N) alone. With the introduction of perestroika (“restructuring”) and glasnost (“openness”) in 1985, then-Soviet President Mikhail Gorbachev accelerated the end of the Cold War era and with it the Arctic as an arena of strategic importance. By 1996, the intergovernmental Arctic Council was constituted, comprising the eight Arctic states – Canada, Denmark, Finland, Iceland, Norway, Russia, Sweden, and the US – together with Indigenous permanent participants, observer states, and other entities. The Arctic Council was established to support peaceful scientific collaboration and environmental protection. The Ilulissat Declaration of 2008 re-affirmed the commitment of the five Arctic littoral states to protection of the Arctic marine environment. But this cooperation has always been in the context of the (preferably sustainable) exploitation and use of the region’s natural resources, including the hydrocarbons whose combustion and resulting emissions are responsible for anthropogenic climate change. What has followed is a period wherein the increasing significance of Arctic amplification – the fact that climate-change impacts manifest sooner and with larger magnitude in the Arctic – is widely recognized. Arctic amplification, as evidence of anthropogenic climate change and of its profound consequences, has raised the stakes in forestalling climate change. But it also challenges the conception of the Arctic as a sacrifice zone. The trade-offs have become both more apparent and less acceptable. What, then, should be our understanding of the common good in the Arctic? The common good, in the widest possible sense, is a commitment to the dignity of life. There is no universal definition of dignity; it is contingent on values. As a result, decision makers seldom agree on valid and appropriate means to achieve dignity. Rather, the social process of identifying and pursuing the common good calls for balancing progress toward dignity against the potential for loss. This balancing act is subject to competing claims within any given context – as in the Arctic. High stakes provoke a higher standard for science and any knowledge relevant to decision making. Concentrations of power, wealth, and other values support alternative interpretations of what constitutes the common good, what can be considered progress toward it, and what losses can be accommodated. But even when there is consensus over what is at stake and what outcomes are preferred, any loss will constitute a sacrifice – voluntary or not, or even by default. Furthermore, at any scale, what we are willing to sacrifice is influenced by what we see or experience directly and by what seems far, irrelevant, or inconsequential. And when the stakes are high, sacrifice of the remote is even more readily justified. This is a key observation in the context of climate change, where environmental and other impacts are often concentrated in regions and among communities that are remote from the individuals, organizations, and governments whose behavior facilitates high-stakes loss and damage. In 2022, assessments of the common good in and for the Arctic are evolving as rapidly as the biophysical environment. The accelerating retreat of ice on land and at sea is raising expectations for both new opportunities and new challenges in hydrocarbon exploitation, international shipping, infrastructure development, fisheries, and tourism. The invasion of Ukraine by Russia has profound consequences for the Arctic as sanctions affect the Russian-administered Northern Sea Route. Economic development by and for Arctic peoples is coupled with an influx of mid-latitude actors, vying for primacy in the Race to the North. Identifying and appraising trade-offs is challenging. One must account for diverse factors and conditions, including the historical inequities accruing from colonial exploitation and the current aspirations of Arctic peoples. Nature responds dramatically to our past actions and our inability, now, to act. Multiple converging forces in the Arctic region are increasing the stakes for the world. The Arctic is no longer remote.
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 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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.017 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| 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".