Community perspectives on the environmental impacts of Arctic shipping: Case studies from Russia, Norway and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Communities across the Arctic are experiencing growth in transiting, destination and domestic ship traffic. Environmental impacts resulting from Arctic shipping have been well documented, but little is known about how these impacts affect livelihoods and adaptive capacity of the local communities that are reliant on their natural landscapes. Given the heterogeneity of the Arctic, this study applied a community-based approach to empirically assess the impacts of shipping on the environment. Interviews were conducted in three island communities: Solovetsky in Russia (n = 24), Longyearbyen on Svalbard, Norway (n = 22) and Cambridge Bay, Canadian Arctic (n = 24). Despite differences in the trends of shipping activities that occur in each of the case study communities, there was consensus regarding significant environmental impacts from ship traffic on the natural environment, and that these in turn present a great concern for community livelihoods. The concerns differ greatly among the three communities and depended on the local context and perceptions and use of the natural environment. We conclude that the natural environment represents a salient determinant of adaptive capacity in the context of growing ship traffic across the Arctic. Moreover, this context-dependent determinant varies in the way it is perceived across case communities.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| 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 it