My Critique is Bigger than Yours: Constituting Exclusions in Critical Security Studies
Bibliographic record
Abstract
Critical Security Studies proceeds from the premise that words are world-making, that is that the ways we think about security are constitutive of the worlds of security we analyse. Turned to conventional security studies and the practices of global politics, this critical insight has revealed the ways in which the exclusions that are the focus of this conference have been produced. Perhaps most notable in this regard has been David Campbell's work, showing how the theory and practice of security are an identity discourse producing both insides and outsides, but the production of excluded others is a theme that runs through the critical scholarship on security in the past decade or more. This article turns the critical security studies gaze on itself, to explore the field's own complicity in the production of exclusions. The article reads three important instances of critical security studies for the inclusions and exclusions they produce: Ken Booth's Theory of World Securitv, the epilogue to David Campbell's Writing Security, and the CASE Collective Manifesto. The article concludes by asking about the nature of the inclusions and exclusions these divisions produce and the politics which those exclusions, in turn, (re)produce.
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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 | 0.024 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.096 |
| Scholarly communication | 0.018 | 0.017 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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".