Arctic roads and railways: social and environmental consequences of transport infrastructure in the circumpolar North
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
Land-based transport corridors and related infrastructure are increasingly extending into and across the Arctic in support of resource development and population growth, causing large-scale cumulative changes to northern socio-ecological systems. These changes include the increased mobility of people, goods and resources, and environmental impacts on landscapes and ecosystems as the human footprint reaches remote, unindustrialized regions. Arctic climate change is also generating new challenges for the construction and maintenance of these transport systems, requiring adaptive engineering solutions as well as community resilience. In this review article, we consider the complex entanglements between humans, the environment, and land transportation infrastructure in the North and illustrate these interrelations by way of seven case studies: the Baikal–Amur Mainline, Bovanenkovo Railway, Alaska–Canada Highway, Inuvik–Tuktoyatuk Highway, Alaska Railroad, Hudson Bay Railway, and proposed railways on Baffin Island, Canada. As new infrastructure is built and anticipated across the circumpolar North, there is an urgent need for an integrated socio-ecological approach to impact assessment. This would include full consideration of Indigenous knowledge and concerns, collaboration with local communities and user groups in assessment, planning and monitoring, and evaluation of alternative engineering designs to contend with the impacts of climate change in the decades ahead.
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.
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 | 0.001 |
| Science and technology studies | 0.002 | 0.008 |
| 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