Creating a secure cyberspace – Securitization in Internet governance discourses and dispositives in Germany and Russia
Bibliographic record
Abstract
This article deals with the phenomenon of securitization in the emerging policy field of Internet governance. In essence, it presents a combination of theoretical reflections preparing the grounds for a comparative analysis of respective discourses and so-called dispositives as well as preliminary findings from such a comparative project. In the following sections we firstly present some theoretical reflections on the structural conditions of Internet regulation in general and the role and relevance of securitization in particular. Secondly, we shed light on how securitization is constructed and how it might affect the build-up process of instruments of Internet regulation. How does securitization happen, how does it work in different societies/states? Which discursive elements can be identified in elites’ discourses? And which politico-legal dispositives do emanate from discourse? In a third section we illustrate our reflections with some preliminary findings from a comparison of cybersecurity discourses and dispositives in Germany and Russia.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.020 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".