Bibliographic record
Abstract
The recent and continuing changes in Southeast Asia - the economic calamity in 1997-98, the overthrow of President Soeharto's New Order and the tenuous establishment of democracy, and the horrific circumstances of East Timor's independence - have disturbed Australia's security situation more seriously than anything since the 1960s, when Australia was at war (albeit covertly) with Indonesia in Borneo and had a task force in Vietnam. The rate of technological change is also unprecedented, especially in the area of information technology (IT) and its manifold applications, promising a revolution in military affairs (RMA), some aspects of which are very attractive for Australian defence planning. At the same time, the Australian Defence Force (ADF) faces the imminent prospect of 'block obsolescence' - when major platforms such as the F/A-18 Hornet multi-role fighter aircraft, the F-111 strike fighters, the P-3C Orion long-range maritime patrol aircraft, and all of the navy's surface combatants, will need to be replaced (or their tasks foregone). Addressing these issues will require the development of a sound appreciation of Australia's security environment, and of clear and coherent strategic guidance for defence force planning. The purpose of this volume is to assist and inform these processes.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".