Unmaking militarized masculinity: veterans and the project of military-to-civilian transition
Bibliographic record
Abstract
Feminist scholarship on war and militarization has typically focussed on the making of militarized masculinity. However, in this article, we shed light on the process of ‘unmaking’ militarized masculinity through the experiences of veterans transitioning from military to civilian life. We argue that in the twenty-first century, veterans’ successful reintegration into civilian society is integral to the legitimacy of armed force in Western polities and is therefore a central concern of policymakers, third-sector service providers, and the media. But militarized masculinity is not easily unmade. Veterans often struggle with their transition to civilian life and the negotiation of military and civilian gender norms. They may have an ambivalent relationship with the state and the military. Furthermore, militarized masculinity is embodied and experienced, and has a long and contradictory afterlife in veterans themselves. Attempts to unmake militarized masculinity in the figure of the veteran challenge some of the key concepts currently employed by feminist scholars of war and militarization. In practice, embodied veteran identities refuse a totalizing conception of what militarized masculinity might be, and demonstrate the limits of efforts to exceptionalize the military, as opposed to the civilian, aspects of veteran identity. In turn, the very liminality of this ‘unmaking’ troubles and undoes neat categorizations of military/civilian and their implied masculine/feminine gendering. We suggest that an excessive focus on the making of militarized masculinity has limited our capacity to engage with the dynamic, co-constitutive, and contradictory processes which shape veterans’ post-military lives.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.042 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".