Bibliographic record
Abstract
In this thematic issue, six papers and three short commentaries investigate the evolving nature of borders in the Arctic in an era of climate change and globalization. Together, they illustrate how processes unique to the Arctic, such as sea ice melt and Inuit self-governance, tell a larger story about the co-evolving relationship of people and the environment, and the physical and constructed borders that give them meaning. Arctic human–environment relations are embedded in distinct histories and materialities in which border-making is understood as a multi-scalar arena of subnational and transnational actors, rather than the exclusive domain of the state. At the same time, the Arctic is shaped by powerful agents of change whose impacts span national borders and reconfigure environmental barriers. The papers in this issue reveal the ways in which Arctic climatic, political, economic, and demographic change amount to a transformation in thinking about Arctic borders and bordered spaces. We hope that the Arctic case will stimulate further investigation in borderlands around the world undergoing similarly transformative changes to physical and human systems.
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".