Preface (1999) Preface (1990) 1. Subjects of Sex/Gender/Desire I. 'Women' as the Subject of Feminism II. The Compulsory Order of Sex/Gender/Desire III. Gender: The Circular Ruins of Contemporary Debate IV. Theorizing the Binary, the Unitary and Beyond V. Identity, Sex and the Metaphysics of Substance VI. Language, Power and the Strategies of Displacement 2. Prohibition, Psychoanalysis, and the Production of the Heterosexual Matrix I. Structuralism's Critical Exchange II. Lacan, Riviere, and the Strategies of Masquerade III. Freud and the Melancholia of Gender IV. Gender Complexity and the Limits of Identification V. Reformulating Prohibition as Power 3. Subversive Bodily Acts I. The Body Politics of Julia Kristeva II. Foucault, Herculine, and the Politics of Sexual Discontinuity III. Monique Wittig - Bodily Disintegration and Fictive Sex IV. Bodily Inscriptions, Performative Subversions Conclusion - From Parody to Politics

Postmodern Subjects, Postmodern BodiesThinking Fragments: Psychoanalysis, Feminism, and Postmodernism in the Contemporary WestYearning: Race, Gender, and Cultural PoliticsGender Trouble: Feminism and the Subversion of Identity

Based on two years of fieldwork and over 100 interviews, we analyze mixed martial arts fighters’ fears, how they managed them, and how they adopted intimidating personas to evoke fear in opponents. We conceptualize this process as ‘‘managing emotional manhood,’’ which refers to emotion management that signifies, in the dramaturgical sense, masculine selves. Our study aims to deepen our understanding of how men’s emotion work is gendered and, more generally, to bring together two lines of research: studies of gendered emotion management and studies of emotional identity work. We further propose that managing emotional manhood is a dynamic and trans-situational process that can be explored in diverse settings.

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Managing Emotional Manhood Fighting and Fostering Fear in Mixed Martial Arts

In recounting some of the key sociological insights offered by over 30 years of research on emotion management, or emotion regulation, we orient our discussion around sociological answers to the fo...

Emotion Management: Sociological Insight into What, How, Why, and to What End?

We find that only 17% of FTSE 100 company websites refer directly to transgender (‘trans’) individuals, illustrating the extent to which trans voices are unheard in the workplace. We propose that these voices are missing for a number of reasons: voluntary silence to protect oneself from adverse circumstances; the subsumption of trans voices within the larger ‘LGBT’ community; assimilation, wherein many trans voices become affiliated with those of their post-transition gender; multiple trans voices arising from diversity within the transgender community; and limited access to voice mechanisms for transgender employees. We identify the negative implications of being unheard for individual trans employees, for organizational outcomes, and for business and management scholarship, and propose ways in which organizations can listen more carefully to trans voices. Finally, we introduce an agenda for future research that tests the applicability of the theoretical framework of invisible stigma disclosure to transgender individuals, and calls for new theoretical and empirical developments to identify HRM challenges and best practices for respecting trans employees and their choices to remain silent or be heard.

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Listen carefully: transgender voices in the workplace

To date, little research has systematically investigated perceptions of mental health professionals regarding motivations for self-injury among prison inmates. To help fill this gap, the authors used descriptive techniques to examine self-injurious behavior among inmates from the perspective of correctional mental health professionals. A quantitative survey assessed perceptions of mental health staff regarding etiology, motivations, and manifestations of self-injury. A qualitative interview component was used to explicate responses from the survey. Inmate cutting, scratching, opening old wounds, and inserting objects were the most commonly witnessed behaviors. Findings suggest that self-injury occurred regularly and that a subset of inmates are responsible for recurrent events. Mental health professionals perceived the motivation for inmate self-injury to be both manipulative and a coping mechanism. They described current management strategies and corresponding needs for training and resources.

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Institutional Responses to Self-Injurious Behavior Among Inmates:

Much research has shown that entering the public sphere is emotionally taxing yet key to male-to-female transsexuals’ status passage. Yet, little is known about how transsexuals actively manage their emotions during this important transitional phase. Taking a dramaturgical approach to emotions, we explored how some male-to-female transsexuals managed their emotions in ways that helped generate self-confidence and commitment to their paths. Interviewees engaged in three primary forms of emotion work: (1) preparatory emotion work mitigated anxiety and bolstered confidence, which motivated them to enter public arenas as women; (2) in situ emotion work transformed negative emotions as they arose when performing womanhood in public; and (3) retrospective emotion work reinterpreted past public performances to neutralize negative and accentuate positive emotions.

Emotion work in the public performances of male-to-female transsexuals.

Although self-injury is not a new behavior, public awareness of it has increased dramatically since the mid-1990s (Adler and Adler, 2005). Selfinjury is generally defined as the deliberate act of physically hurting oneself, usually without conscious suicidal intent, in a manner that results in superficial, rather than traumatic, damage to body tissue. Despite typically being perceived as psychological in nature (Favazza, 1998; Muehlenkamp, 2005), the etiology is not often clear. The bulk of selfinjury behavior (SIB) research comes from a mental health perspective, rather than from sociology or related disciplines; yet the DSM IV (1994) says little about SIB, other than listing it as a symptom for other “disorders.” Clinically, self-injury consistently has been linked to a broad range of individual-level problems, ranging from intellectual and developmental difficulties to emotional dysfunctions, and to physical and behavioral maladaptation. Such typologies reduce the act to individual pathology rather than, as Kilty (2006) notes, a possible coping mechanism in a debilitating environment. Estimates of the prevalence of self-injury in the non-prisoner population are inconsistent, varying from 1% to 4% and between 12% to over 40% among adolescents and college-aged samples (Muehlenkamp, 2005; White Kress, 2003). One of the few common claims across studies is that selfinjury typically begins during early adolescence and tends to persist for an average of 10 to 15 years, although it may continue for decades (Favazza, 1998; Muehlenkamp, 2005).

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Self‐injury in correctional settings: “pathology” of prisons or of prisoners?*

“What I Had to Do to Survive”:: Self-Injurers’ Bodily Emotion Work

Background The clinical narrative in electronic health records (EHRs) carries valuable information for predictive analytics; however, its free-text form is difficult to mine and analyze for clinical decision support (CDS). Large-scale clinical natural language processing (NLP) pipelines have focused on data warehouse applications for retrospective research efforts. There remains a paucity of evidence for implementing NLP pipelines at the bedside for health care delivery. Objective We aimed to detail a hospital-wide, operational pipeline to implement a real-time NLP-driven CDS tool and describe a protocol for an implementation framework with a user-centered design of the CDS tool. Methods The pipeline integrated a previously trained open-source convolutional neural network model for screening opioid misuse that leveraged EHR notes mapped to standardized medical vocabularies in the Unified Medical Language System. A sample of 100 adult encounters were reviewed by a physician informaticist for silent testing of the deep learning algorithm before deployment. An end user interview survey was developed to examine the user acceptability of a best practice alert (BPA) to provide the screening results with recommendations. The planned implementation also included a human-centered design with user feedback on the BPA, an implementation framework with cost-effectiveness, and a noninferiority patient outcome analysis plan. Results The pipeline was a reproducible workflow with a shared pseudocode for a cloud service to ingest, process, and store clinical notes as Health Level 7 messages from a major EHR vendor in an elastic cloud computing environment. Feature engineering of the notes used an open-source NLP engine, and the features were fed into the deep learning algorithm, with the results returned as a BPA in the EHR. On-site silent testing of the deep learning algorithm demonstrated a sensitivity of 93% (95% CI 66%-99%) and specificity of 92% (95% CI 84%-96%), similar to published validation studies. Before deployment, approvals were received across hospital committees for inpatient operations. Five interviews were conducted; they informed the development of an educational flyer and further modified the BPA to exclude certain patients and allow the refusal of recommendations. The longest delay in pipeline development was because of cybersecurity approvals, especially because of the exchange of protected health information between the Microsoft (Microsoft Corp) and Epic (Epic Systems Corp) cloud vendors. In silent testing, the resultant pipeline provided a BPA to the bedside within minutes of a provider entering a note in the EHR. Conclusions The components of the real-time NLP pipeline were detailed with open-source tools and pseudocode for other health systems to benchmark. The deployment of medical artificial intelligence systems in routine clinical care presents an important yet unfulfilled opportunity, and our protocol aimed to close the gap in the implementation of artificial intelligence–driven CDS. Trial Registration ClinicalTrials.gov NCT05745480; https://www.clinicaltrials.gov/ct2/show/NCT05745480

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Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults

Margaret Leaf

Papers

Emotion work in the public performances of male-to-female transsexuals.

Self‐injury in correctional settings: “pathology” of prisons or of prisoners?*

“What I Had to Do to Survive”:: Self-Injurers’ Bodily Emotion Work

Deployment of Real-time Natural Language Processing and Deep Learning Clinical Decision Support in the Electronic Health Record: Pipeline Implementation for an Opioid Misuse Screener in Hospitalized Adults