Securing the Political Imagination: Popular Culture, the Security Dispositif and the Biometric State
Bibliographic record
Abstract
Abstract What is the relationship between popular culture and the reliance on risk management as a framework for governance in the emerging security dispositif? Furthermore, how is one to understand the influence of culture and cultural forces in relation to the emerging biometric state and the alleged security imperatives therein? This article contends that the emerging security dispositif, and the associated imaginations and cultural performances that sustain and shape it, are vital to the production of what is referred to here as the 'biometric state'. Motivated by an obsession with technologies of risk and practices of risk management, the biometric state is defined by the prevalence of virtual borders and reliance on biometric identifiers such as passports, trusted-traveller programmes and national ID cards, as well as the forms of social sorting that accompany these manoeuvres. Raising the marriage of convenience that connects two related dispositifs of security — geopolitics and biopolitics — the article considers the relationship between their referent objects: the state and everyday life, respectively. More specifically, popular culture integral to sustaining the emerging security dispositif forms the core of the analysis, as the article asserts the constitutive possibilities of popular culture.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.042 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".