“Freeze my Semen and I Will Join the War”: The Masculinization of the Security–Demography Nexus
Bibliographic record
Abstract
Abstract This article explores and theorizes an aspect of war in the 2020s that has not previously been recognized in social science literature: The practice of soldiers freezing their semen before joining the military. The security–demography nexus has been studied mainly as a state concern—whether a state should limit or expand its population depending on different factors. In this context, women have been the main targets of biopolitical reproduction efforts. However, societal and political shifts, coupled with advancements in reproductive technology that enhance accessibility, necessitate a re-evaluation of the gendered dynamics within the security–demography relationship. The war between Russia and Ukraine represents an unusual example of two industrialized states involved in an interstate war. The practice of soldiers freezing their semen constitutes a new masculinization of the security–demography nexus. We argue that the theoretical concept of reproductive insurance implies a form of self-governance that can manage shifting masculinities in ways that allow the male individual to protect the capacity to have children before risking life on the battlefield. The shifting gender dynamic of the security–demography nexus means that Western militaries may have to adapt their policies and offer reproductive insurance to both women and men within their ranks.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".