Secondary victims of rape

Rape is often a very traumatic experience, which affects not only the primary victim (PV) but also his/her significant others. Studies on secondary victims of rape are few and have almost exclusively studied male partners of female rape victims. This study examined the impact of rape on 107 secondary victims, including family members, partners, and friends of male and female rape victims. We found that many respondents found it difficult to support the PV and that their relationship with the PV was often affected by the assault. Furthermore, the sample showed significant levels of traumatization, and it was estimated that approximately one quarter of the respondents suffered from posttraumatic stress syndrome (PTSD). Degree of traumatization was associated with a more recent assault, higher efforts to support the PV, recurrent thoughts about having been able to prevent the assault, a lack of social support for the respondent, and feeling let down by others. The respondents were generally interested in friend-, family-, and partner-focused interventions, particularly in receiving education about how best to support a rape victim.     

‘A ondi queras’: Ranchero identity construction by U.S. born Mexicans on Facebook

This study describes how transnational second‐generation Mexican bilinguals use a stigmatized variety of Mexican Spanish to communicate on Facebook and construct an identity. The stereotyped features of this variety index a ranchero identity. Historically, ranchero is an ambivalent identity for Mexican society in general. On the one hand, ranchero culture is a positive reminiscence of Mexico's agrarian past, while on the other, rancheros, along with indigenous Mexicans, are at the bottom of the hierarchy in Mexican society. A discourse‐centered, ethnographic analysis of digitally mediated conversations demonstrates how language use allows participants to reminisce about their collective past, maintain Mexican identities tied to their ancestors, fit their identities to contemporary U.S. Mexican culture, and distance themselves from the stigma associated with the ranchero background.     

A decision support methodology for strategic planning in maritime transportation

This paper presents a decision support methodology for strategic planning in tramp and industrial shipping. The proposed methodology combines simulation and optimization, where a Monte Carlo simulation framework is built around an optimization-based decision support system for short-term routing and scheduling. The simulation proceeds by considering a series of short-term routing and scheduling problems using a rolling horizon principle where information is revealed as time goes by. The approach is flexible in the sense that it can easily be configured to provide decision support for a wide range of strategic planning problems, such as fleet size and mix problems, analysis of long-term contracts and contract terms. The methodology is tested on a real case for a major Norwegian shipping company. The methodology provided valuable decision support on important strategic planning problems for the shipping company.     

Multistate models in health insurance

We illustrate how multistate Markov and semi-Markov models can be used for the actuarial modeling of health insurance policies, focusing on health insurances that are pursued on a similar technical basis to that of life insurance. In the first part, we give an overview of the basic modeling frameworks that are commonly used and explain the calculation of prospective reserves and net premiums. In the second part, we discuss the biometric insurance risk, focusing on the calculation of implicit safety margins. We present new results on implicit margins in the semi-Markov model and on biometric estimation risk in the Markov model, and we explain why there is a need for future research concerning the systematic biometric risk.     

Fitting Weibull duration models with random effects

Duration time models often should include correlated failure times, due to clustered data. These random effects hierarchical models sometimes are called frailty models when used for survival analyses. The data analyzed here involve such correlations because patient level outcomes (the times until graft failure following kidney transplantation) are observed, but patients are clustered in different transplant centers. We describe fitting such models by combining two kinds of software, one for parametric survival regression models, and the other for doing Poisson regression in a hierarchical setting. The latter is implemented by using PRIMM (Poisson Regression and Interactive Multilevel Modeling) methods and software (Christiansen & Morris, 1994a). An illustrative example for profiling data is included withk=11 kidney transplant centers andN=412 patients.     

Catching a glimpse: Corona‐life and its micro‐politics in academia

The spread of COVID‐19 acutely challenges and affects not just economic markets, demographic statistics and healthcare systems, but indeed also the politics of organizing and becoming in a new everyday life of academia emerging in our homes. Through a collage of stories, snapshots, vignettes, photos and other reflections of everyday life, this collective contribution is catching a glimpse of corona‐life and its micro‐politics of multiple, often contradicting claims on practices as many of us live, work and care at home. It embodies concerns, dreams, anger, hope, numbness, passion and much more emerging amongst academics from across the world in response to the crisis. As such, this piece manifests a shared need to — together, apart — enact and explore constitutive relations of resistance, care and solidarity in these dis/organizing times of contested spaces, identities and agencies as we are living–working–caring at home during lockdowns.