The minister, the Commandant and the cadets: Scandal and the mediation of Australian civil–military relations
Bibliographic record
Abstract
The Australian Defence Force (ADF) has recently undergone the most comprehensive review of its organizational culture since federation. Western militaries across the USA, Canada and the UK are similarly engaged. Military misconduct, including rape, assault and the long traditions of hazing and bastardization, have been increasingly exposed, engaging civil society, agitating government and undermining military integrity. The Skype Affair is described as a particularly important military misconduct scandal that brought these relations, and ruling relations more specifically, into focus. The article describes the contest over democratic control of the armed forces initiated when the jurisdictions and authority of the Defence Minister, the Chief of Defence and the Commandant of the Australian Defence Force Academy (ADFA) converged over the management of this military scandal. This article looks at how relations between Australian civil society, the military and the state are affected by the varying engagements of these sectors with the question of violence in the military and, subsequently, military modernization. The news-mediated discourse is one that highlights the structural split of civil–military relations, between two white masculinized institutions in a context of distinct cultural divergence over the rule of nation.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.035 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".