Norwegian Blues? Rethinking the Idea of Middle Powers in an Era of Fuzzy Bifurcation
Bibliographic record
Abstract
ABSTRACT Unsuccessful efforts to update the middle power concept for the contemporary international system have prompted calls for the concept to be “historicized”—to be retired from common use and treated as a purely historical term. The problem with this proposal is that “middle power” has become increasingly popular in the 2020s in analysis, commentary, and state practice. The purpose of this article is to offer an alternative to historicization. While we acknowledge that the traditional understanding of middle power was deeply rooted in the twentieth century, and particularly in that era of American hegemony during the Cold War and post–Cold War eras, the continued use of the term suggests that we need to embrace the flexibility that has always been associated with the concept. This paper calls for a return to a variant of the nineteenth‐century idea that middle powers were located geographically “in the middle” between great powers. In the 2020s and 2030s, which we argue is marked by “fuzzy bifurcation,” we propose that middle powers are those located geostrategically “in the middle” between the two great powers of the contemporary international system, the United States and China.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.044 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".