Australia: Maximising Discretion in an Untested Alliance
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
A central feature of Australia's participation in the Australia-US alliance has been Australia's support for US strategic capabilities. Australia provides support for US capabilities through joint facilities at Pine Gap and elsewhere and through arms control monitoring and treaty verification. 1 Within this framework, Australia comes within the US policy of extended deterrence. This aspect of the Australia-US alliance has not featured prominently in the recent official discourse concerning the alliance, but this is changing due to the return of great power competition in the Indo-Pacific as the major strategic challenge facing Australia. Great power competition brings with it the risk of conflict. Understanding how crises might escalate, including escalation to a potential nuclear conflict, is a central concern for alliance management. This chapter gives a brief overview of Australia's alliance management in recent decades, including the role of deterrence in Australia's defence policy. It suggests some areas where traditional approaches to alliance management may not be fit for the emerging Indo-Pacific strategic environment.
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 | 0.000 | 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