The Experiences of Care Leavers (Post-care Adults) in Social Work Education

This paper explores the experiences of social work students on qualifying degree programmes in the UK who have previously been in care or ‘looked after’. Using a sample drawn from three social work programmes in the North West of England, a semi-structured interview schedule was constructed, with the support of social workers who had been in the care system, to examine the individual journeys of 11 students. This paper aims to explore, with this group of students, how their experiences relate to their decision to apply for a place on a social work course, their experience of admission and the duration of the programme. The paper is of particular relevance to social work educators and makes specific suggestions regarding how current practice in social work education might improve.     

Langevin incremental mixture importance sampling

This work proposes a novel method through which local information about the target density can be used to construct an efficient importance sampler. The backbone of the proposed method is the incremental mixture importance sampling (IMIS) algorithm of Raftery and Bao (Biometrics 66(4):1162–1173, 2010), which builds a mixture importance distribution incrementally, by positioning new mixture components where the importance density lacks mass, relative to the target. The key innovation proposed here is to construct the mean vectors and covariance matrices of the mixture components by numerically solving certain differential equations, whose solution depends on the local shape of the target log-density. The new sampler has a number of advantages: (a) it provides an extremely parsimonious parametrization of the mixture importance density, whose configuration effectively depends only on the shape of the target and on a single free parameter representing pseudo-time; (b) it scales well with the dimensionality of the target; (c) it can deal with targets that are not log-concave. The performance of the proposed approach is demonstrated on two synthetic non-Gaussian densities, one being defined on up to eighty dimensions, and on a Bayesian logistic regression model, using the Sonar dataset. The Julia code implementing the importance sampler proposed here can be found at https://github.com/mfasiolo/LIMIS.     

How Asymptomatic Transmission Influences Mitigation and Suppression Strategies during a Pandemic

Asymptomatic transmission complicates any public health strategies to combat a pandemic, which proved especially accurate in the case of COVID-19. Although asymptomatic cases are not unique to COVID-19, the high asymptomatic case rate raised many problems for developing effective public health interventions. The current modeling effort explored how asymptomatic transmission might impact pandemic responses in four key areas: isolation procedures, changes in reproduction rate, the potential for reduced transmission from asymptomatic cases, and social adherence to public health measures. A high rate of asymptomatic cases effectively requires large-scale public health suppression and mitigation procedures given that quarantine procedures alone could not prevent an outbreak for a virus such as SARS-CoV-2. This problem only becomes worse without lowering the effective reproduction rate, and even assuming the potential for reduced transmission, any virus with a high degree of asymptomatic transmission will likely produce a pandemic. Finally, there is a concern that asymptomatic individuals will also refuse to adhere to public health guidance. Analyses indicate that, given certain assumptions, even half of the population adhering to public health guidance could reduce the peak and flatten the curve by over 90%. Taken together, these analyses highlight the importance of taking asymptomatic cases into account when modeling viral spread and developing public health intervention strategies.     

Retrospective accounts of first exposure to minoritized sexual and gender identities

Although there has been considerable research about attitudes towards LGBTQ+ people, there has been little research into how people first come to be aware of minoritized sexual and gender minority (SGM) identities. This study sought to address this gap. A sample of sexual minority (n = 150) and heterosexual (n = 802) young adults (N = 952; M_age = 18.88 years, SD = 1.75; 949 were cisgender, three were transgender), primarily recruited from a large southern university, were asked retrospectively to recount their first exposure to or awareness of SGM identities. Responses between SGM and heterosexual participants were compared through a variety of analytical approaches, including analyzing themes about the source from which participants first recalled encountering these identities, and whether understanding about these identities came through a personal connection to someone with these identities. SGM participants reported encountering minoritized sexual identities a year earlier than did heterosexual participants, with both groups encountering these concepts in middle childhood, on average. SGM participants were more likely than heterosexual participants to report learning about minoritized gender identities from someone with a minoritized gender identity, while heterosexual participants more often reported learning about these identities from media or celebrities. Heterosexual (vs. SGM) participants were also more likely to imply that minoritized gender identities were adopted to be popular, rather than being authentic identities in themselves. Framed by developmental intergroup theory (DIT), we discuss implications of these findings, especially potential interrelationships with the development of prejudiced attitudes about SGM identities.