Bibliographic record
Abstract
This paper describes the development of the Australian Joint Essential Tasks (AS JETs) list. These tasks were developed to support the planning for, and evaluation of, Joint Exercises. This approach is consistent with that of Australia's allies, who have been operating with such lists for a number of years. The United States' Universal Joint Task List (UJTL) was developed with an emphasis on training. In contrast, the United Kingdom and Canada have taken an enterprise-wide approach, capturing all core Defence tasks. While this approach has the benefit of encompassing the activities of the entire organization, it was believed that a more focused task list was required for Australian joint operations. The AS JETs were developed in line with current Australian doctrine, standard operating procedures, and emerging doctrinal concepts. They consist of a three-level hierarchy that is consistent with current command structures and represents the essential activities to be completed when conducting an operation. Also, the AS JETs were developed through close consultation with representatives from all levels of the Australian Defence Force (ADF). To remain consistent with the ADF's standard practice the AS JETs were designed to be a robust list capturing the tasks that need to be done, rather than specifying how to complete the tasks. It is, however, acknowledged that it is possible to change the AS JETs in both an evolutionary and revolutionary manner. This paper looks at two possible changes that may impact on the AS JETs. The concept of the Strategic Corporal suggests that the focus of the tasks may need to change to accommodate the fact that operations by low-level tactical units can have strategic consequences. With Ubiquitous C2 the scope of the AS JETs at an operational level may decrease, or disappear entirely.
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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 | 0.047 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".