Is the problem with military culture one of bad apples or bad orchards?: war crimes, scandals, and persistent dysfunction
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
This article examines the historic and current role of ‘culture’ in Australian Defence Forces’ responses to scandals, war crimes, and illicit behaviours. It makes the case that the ADF has moved from arguing that illicit activities are the product of isolated soldiers, to arguing that illicit activities are the result of ‘rogue’ groups of soldiers. We call this a shift from the ‘bad apples’’ to the ‘bad orchard’ thesis. Drawing on the concepts of camouflage and building a theoretical understanding of military exceptionalism, we argue we argue ‘military culture’ provides covering fire and camouflage for the institution to protect it from public scrutiny and to hide systemic dysfunction. We also engage with our understanding of institutional gaslighting, to argue that strategies to dismiss and legitimize dysfunction serve to gaslight civilians raising concerns about military conduct by rendering their concerns inexpert, illegitimate, unfounded, or hostile.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| 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