Entangled bodies: Reimagining women’s chronic pain experience in the military through a new materialist perspective
Bibliographic record
Abstract
Women in military contexts navigate chronic pain shaped by intersecting social, institutional, and material factors. Military institutions, grounded in masculine ideals, often exacerbate these challenges, influencing how pain is experienced, managed, and communicated. Chronic pain among women is frequently dismissed or pathologized, compelling them to conform to medical expectations to be taken seriously. Gender, ethnicity, socio-economic status, and migration further compound these experiences. Additionally, military women shoulder gendered caregiving roles and may face personal or systemic trauma, deepening their vulnerabilities. Their bodies are enmeshed in military systems, technologies, and equipment, creating dynamic entanglements that influence pain. This article examines how these complexities shape chronic pain among military women and how an ethics of care can foster systemic change. By exploring the interplay of physiology, psychology, and social dimensions in militarized environments, this article advocates for compassionate and intersectional approaches to addressing chronic pain. Through this lens, it seeks to highlight the unique experiences of military women and promote culture change for improved care and well-being.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.034 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| 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".