Security, economy, population: The political economic logic of liberal exceptionalism
Bibliographic record
Abstract
Abstract In an era in which scholars have become increasingly skeptical about the concept of exceptionalism, this article argues that instead of rejecting it, we should rework it: moving beyond seeing it primarily as a security practice by recognizing the crucial role of political economic exceptionalism. Drawing on Foucault’s later lectures on security, population, and biopolitics, this article suggests that we can understand exceptionalist moves in both security and economic contexts as efforts to manage and secure a population. Focusing on three key moments in the production of exceptional politics – defining the limit of normal politics, suspending the norm, and putting the exception into practice – I examine the parallels, intersections, and tensions between political economic and security exceptionalism, using the concept of economic exceptionalism to make sense of the 2008 global financial crisis. Taking seriously Foucault’s insights into the political economic character of liberal government holds out the promise of providing scholars in the fields of both critical security studies and cultural political economy with a richer understanding of the complex dynamics of exceptionalist politics – a promise that is particularly valuable at the present political juncture.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.066 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".