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 The complexity of the twenty-first century threat landscape contrasts significantly with the bilateral nuclear bargaining context envisioned by classical deterrence theory. Nuclear and conventional arsenals continue to develop alongside antisatellite programs, autonomous robotics or drones, cyber operations, biotechnology, and other innovations barely imagined in the early nuclear age. The concept of cross-domain deterrence emerged near the end of the George W. Bush administration as policymakers and commanders confronted emerging threats to vital American military systems in space and cyberspace. The Pentagon now recognizes five operational environments or so-called domains (land, sea, air, space, and cyberspace), and cross-domain deterrence poses serious problems in practice. This book steps back to assess the theoretical relevance of cross-domain deterrence for the field of international relations. As a general concept, cross-domain deterrence posits that the ways in which actors choose to deter affects the quality of the deterrence they achieve. Contributors to this book include senior and junior scholars and national security practitioners. Their chapters probe the analytical utility of cross-domain deterrence by examining how differences across, and combinations of, different military and nonmilitary instruments can affect choices and outcomes in coercive policy in historical and contemporary cases.
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 | 0.000 | 0.000 |
| 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 | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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