The cross-colonization of finance and security through lists: Banking policing in the UK and India
Bibliographic record
Abstract
Targeted financial sanctions regimes and regulations on ‘dirty money’ put banks on the front line in securing financial circulation. This is the context in which banking actors face the challenge of juggling with hundred of sanction, watch and regulatory lists. In light of that list mania for banking policing, list appears to have become the security device of choice in the everyday life of the financial industry across the world. Instead of reducing the complexity of security-finance dynamics to a zero-sum game (securitization of finance vs financialization of security), the article rather aims to question the critical role of lists in the cross-colonization of finance and security. Drawing on empirical research in the United Kingdom and India, the article adopts an ‘analytics of devices’ to think of and analyse banking policing practices through the instrumentation that makes these practices possible and stable over time. It argues that banking appropriation of security lists both (re)configures lists ‘social identity’ and banking actors’ power-relations in the fields of finance and security. Ultimately, the analytical focus on lists appropriation sheds new light on what securing circulation means in finance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".