Bibliographic record
Abstract
On Thin Ice explores the relationship between the Inuit and the modern state in the vast but lightly populated North American Arctic. It chronicles the aspiration of the Inuit to participate in the formation and implementation of diplomatic and national security policies across the Arctic region and to contribute to the reconceptualization of Arctic Security, including the redefinition of the core values inherent in northern defense policy. With the warming of the Earth's climate, the Arctic rim states have paid increasing attention to the commercial opportunities, strategic challenges, and environmental risks of climate change. As the long isolation of the Arctic comes to an end, the Inuit who are indigenous to the region are showing tremendous diplomatic and political skills as they continue to work with the more populous states that assert sovereign control over the Arctic in an effort to mutually assert joint sovereignty across the region Published on the 50th anniversary of Ken Waltz's classic Man, the State and War, Zellen's On Thin Ice is at once a tribute to Waltz's elucidation of the three levels of analysis as well as an enhancement of his famous 'Three Images,' with the addition of a new 'Fourth Image' to describe a tribal level of analysis. This model remains salient in not only the Arctic where modern state sovereignty remains limited, but in many other conflict zones where tribal peoples retain many attributes of their indigenous sovereignty.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".