Contemporary Financial Nationalism in Theory and Practice
Bibliographic record
Abstract
Abstract The 2008 global financial crisis and its aftermath provided fertile soil for criticism of and alternatives to the international liberal order, including the rise of financial nationalism. Contemporary financial nationalism is a view of the world that is nationalist in its motivation for political action, financial in its policy focus, and illiberal in its conception of political economy. At the same time, it is fundamentally shaped by its emergence from within the international liberal order, which both constrains the policy options of financial nationalists and provides opportunities for them to draw on transnational financial resources and institutions to advance nationalist causes. This article offers a conceptual analysis of contemporary financial nationalism that explores its fundamental characteristics, explains what is distinctive about it, delineates its four major policy subtypes, identifies the resources and capabilities required to successfully engage in it, and discusses the implications of doing so. It aids researchers in thinking about financial nationalism’s internal workings across different contexts, in understanding why it has lasted as long and spread as far as it has, in considering how it may evolve, and in contemplating how it can affect domestic and international political economies.
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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.062 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".