Social Practices of Rule-Making for International Law in the Cyber Domain
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
Abstract In 2013, despite deteriorating relations between Russia and the United States and increased global contention over cybersecurity issues, participating states in the First Committee of the United Nations General Assembly agreed on a landmark report endorsing the applicability of existing international law to state military use of information technology. Given these conditions, the timing of this agreement was surprising. In this article I argue that state representatives engaged in a rule-governed social practice of applying old rules to new cases, and that the procedural rules governing this practice help to explain the existence, timing, and form of the agreement. They also help to explain further agreements expressed in a follow-on report issued in 2015. The findings of the case study presented here demonstrate that social practices of rule-making are simultaneously rule-governed and politically contested, and that outcomes of these processes have been shaped by specialized rules for making, interpreting, and applying rules. The effectiveness of procedural rules in shaping the outcome of a contentious, complex global security issue suggests that such rules are likely to matter even more in simpler cases dealing with less contentious issues.
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 | 0.003 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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