Sovereignty as new beginnings: Action beyond the liberal subject, among undercover police investigators in Europe, for example
Bibliographic record
Abstract
This article argues that Schmitt's “state of exception” is only one expression of the deeper sovereign phenomenon, specifically the human capacity to inaugurate new beginnings in shared space. Sovereign action thus includes anything from Schmitt's vertically-imposed state of exception, which eliminates political subjecthood, to the thrill of horizontally-arranged movements, which enable it. To make this argument, the article foregoes the idea of the bounded, internally coherent liberal subject in favor of a relational subject, who is both internally divided and inherently tied to others. The subject's instability and relationality make new beginnings possible and renders sovereign action promising, even if risky. An unexpected example of this fuller view of sovereignty appears in an undercover police team in southern Europe that investigates global human smuggling and trafficking rings. Based on extensive ethnographic research, this article shows how they often act on their own ethical judgments, reached by considering the standpoints of people tied to their investigations, rather than through obedience to law, policy, or superior command. Acting outside constitutional order, these investigators, (re)constitute themselves as particular persons through their joint actions and simultaneously constitute modest sovereign spaces, however tentatively.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.031 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| 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".