Bibliographic record
Abstract
Abstract Motivated by the neglect of uncertainty and perverse consequences in constructivist studies of security, this article pursues a reconceptualization of the security dilemma. Approaching the dilemma as a “logic of self-limitation” constituted by choice, uncertainty, and tragedy, the article explores how this logic can be transposed to the constructivist context of securitization theory. The resulting “securitization dilemma” draws renewed attention to the unintended character of social life, highlights how the choice to engage in practices of threat construction are shaped by uncertainty, and shows how the failure to recognize these limitations can have tragic consequences. While the argument aims to broaden the empirical focus of securitization studies to include perverse and unintended consequences, it also looks to engage with the literature's distinctive ethical claim over how speaking security is never a neutral act. Political actors may well be responsible for the security claims they make, but we need to recognize that this responsibility includes the effects of security claims that actors anticipate, as well as those they do not.
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 | 0.028 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.108 |
| Scholarly communication | 0.010 | 0.020 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".