What kind of theory – if any – is securitization?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
One of the great appeals of securitization theory, and a major reason for its success, has been its usefulness as a tool for empirical research: an analytic framework capable of practical application. However, the development of securitization has raised several criticisms, the most important of which concern the nature of securitization theory. In fact, the appropriate methods, the research puzzles and type of evidence accepted all derive to a great extent from the kind of theory scholars bequeath their faith to. This Forum addresses the following questions: What type of theory (if any) is securitization? How many kinds of theories of securitization do we have? How can the differences between theories of securitization be drawn? What is the status of exceptionalism within securitization theories, and what difference does it make to their understandings of the relationship between security and politics? Finally, if securitization commands that leaders act now before it is too late, what status has temporality therein? Is temporality enabling securitization to absorb risk analysis or does it expose its inherent theoretical limits?
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.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it