The securitization audience in theologico-political perspective: Giorgio Agamben, doxological acclamations, and paraconsistent logic
Bibliographic record
Abstract
Over the past two decades, securitization theory has developed into a robust literature of cases and critiques. The vast majority of the attention paid to securitization has been to the securitizing actor and the referent object, leaving the audience – the body that determines the fate of a securitizing move by accepting or rejecting the securitizing actor’s request – undertheorized. The audience is presented as a problematic contradiction, because as a collectivity called by the securitizing actor it appears to be a passive body, critiqued thereby as potentially irrelevant. On the other hand, both the original Copenhagen school formulation of securitization theory and many of its current theorists reaffirm the agency of the audience to actively determine the success or failure of the securitizing move. This article turns to political theology for guidance, and explains the contradiction of the passive/active audience through homology to the ekklesia and the acclamation of ‘amen’ in liturgical doxology. The fact that the congregation is passive recipient of a call does not negate the essential and substantial role that it must actively play, just as the contradiction of the passive/active description of the securitization audience is not a problem of illogic, but a paraconsistent truth.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.040 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".