Uniform Identity? Lesbians and the Negotiations of Gender & Sexuality in the British Army since 1950
Abstract: Homosexuality has always been deemed to be incompatible with military service and the British Armed Forces has enforced this policy with some rigour. STatistics for discharges on the grounds of homosexuality show that lesbians in the British Army have been the most targeted group. The ban on homosexuality was lifted in January 2000. The change to military policy means that all gay men and lesbians now have the right to serve in the Armed Forces without fear of persecution. As an organisation constructed as both masculine and heterosexual, the British Army is a place from which women and gay men have been traditionally excluded. This thesis explores how the British Army acted/ acts as the backdrop for the interaction of gender and sexuality within a particular space and time. By exploring the experiences of lesbian soldiers, living and working in the male-dominated environment of the Army, this thesis offers a unique glimpse of how the institutional structures regulate both gender and sexuality by controlling the female military body. Quantitative and qualitative data were gathered from lesbian participants through a combination of questionnaires and semi-structured interviews. My analyses reveal how lesbians made sense of their everyday lives as women and as soldiers and also made visible the strategies they employed to live as lesbians within their 'uniform identity'. This research adds to the body of knowledge about women's experiences of military life by exploring the inter-relationships and tensions between three 'identities' - woman, soldier and lesbian - and places these experiences within the context of the British Army since 1950. These findings illustrate the depth and range of potential areas for investigation and opportunities for further research are discussed.
Abstract: Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use and relapse-critical markers of risk and recovery from opioid use disorder (OUD). In this study, we used natural language processing (NLP) to automate the extraction of opioid relapses, and the timing of these occurrences, from veteran patients' electronic medical record. We then demonstrated the utility of our NLP tool via analysis of pre-/post-COVID-19 opioid relapse trends among veterans with OUD. For this demonstration, we analyzed data from 107,606 veterans OUD enrolled in Veterans Health Administration, comparing a pandemic-exposed cohort (n = 53,803; January 2019-March 2021) to a matched prepandemic cohort (n = 53,803; October 2017-December 2019). The recall of our NLP tool was 75% and our precision was 94%, demonstrating moderate sensitivity and excellent specificity. Using the NLP tool, we found that the odds of opioid relapse postpandemic onset were proportionally higher compared to prepandemic trends, despite patients having fewer mental health encounters from which to derive instances of relapse postpandemic onset. In this research application of the tool, and as hypothesized, we found that opioid relapse risk was elevated postpandemic. The application of NLP Methods: to identify and monitor relapse risk holds promise for future surveillance, risk prevention, and clinical outcome research.