“Oh My God,I Sound Like a Horrible Person”: Generic Processes in the Conditional Acceptance of Sexual and Gender Diversity

This article outlines a generic process in the reproduction of inequality that we name “conditional acceptance.” Based on 20 in‐depth interviews with cisgender, heterosexual Christian women who support same‐sex marriage legalization, supplemented with reviews of LGBT, religious, and inequalities scholarship, we demonstrate how members of dominant groups may maintain boundaries that facilitate the persistence of social inequality by conditionally accepting members of marginalized groups. Specifically, our findings suggest that respondents both created the appearance of tolerance and maintained the devaluation of LGBT people by (1) supporting equality with a few caveats, (2) suggesting acceptance of those who cannot help being abnormal, (3) arguing that social change was not their responsibility, (4) defining sexual and gender difference as a personal choice, and (5) asserting that they could hate the sin while loving the sinner. In conclusion, we argue that examining processes of conditional acceptance may provide insight into (1) the persistence of social inequality despite social movement victories, and (2) the importance of integrating existing scholarship focused on sexual, gendered, and religious boundary maintenance.     

Video Game Use as a Tool for Assessing and Intervening with Identity Formation and Social Development in Family Therapy

Because video games are becoming such an integral part of our culture, modern family therapists are more likely than ever to encounter families with members who play them. It is easy to overlook video game use in terms of its potential as a therapeutic tool, particularly if a therapist possesses only limited knowledge of the medium. Using existing literature and my experience as a lifelong gamer, I provide family therapists with a background of the major video game genres and explain how video games can aid in the assessment of factors such as identity formation and social development. I also provide a systemic case example, recommendations for practice, and a table for quick reference to highlight potential videogame‐based family therapy interventions.     

Using Housing Vouchers to Create Stable Mixed-Income Gentrifying Neighborhoods: A Case Study of Over-the-Rhine,Cincinnati, OH

The Over-the-Rhine (OTR) neighborhood of Cincinnati, Ohio is a gentrifying inner-city community undergoing rapid revitalization. In a gentrifying neighborhood like OTR, the Housing Choice Voucher Program (HCVP) could help sustain a mix of incomes within an increasingly high-income community. This study uses geographic information system analysis to examine the role of HCVP in OTR from 1995 to 2012, that is, changes in voucher holder density, hotspots, and migration patterns. Discussions with key stakeholders provide additional insight on gentrification in OTR and the ways HCVP could be used to create a mixed-income neighborhood that would benefit lower-income households.     

Unpacking intergenerational (IG) programs for policy implications: A systematic review of the literature

Intergenerational care is a program where both the younger and older generations are receiving programmed care in an environment where activities and resources are shared between them. Anecdotally, an intergenerational care program takes on many forms. This paper presents a systematic literature review of intergenerational care models. Our findings are relevant to policy makers as the paper highlights the opportunities to create an age-friendly environment by introducing intergenerational models in Australia, where intergenerational care development is in its infancy. Future research will help articulate the personal, social, and economic value of intergenerational care.     

Almost separable matrices

An \(m\times n\) matrix \(\mathsf {A}\) with column supports \(\{S_i\}\) is k-separable if the disjunctions \(\bigcup _{i \in \mathcal {K}} S_i\) are all distinct over all sets \(\mathcal {K}\) of cardinality k. While a simple counting bound shows that \(m > k \log _2 n/k\) rows are required for a separable matrix to exist, in fact it is necessary for m to be about a factor of k more than this. In this paper, we consider a weaker definition of ‘almost k-separability’, which requires that the disjunctions are ‘mostly distinct’. We show using a random construction that these matrices exist with \(m = O(k \log n)\) rows, which is optimal for \(k = O(n^{1-\beta })\). Further, by calculating explicit constants, we show how almost separable matrices give new bounds on the rate of nonadaptive group testing.     

Naloxone administration for suspected opioid overdose: An expanded scope of practice by a basic life support collegiate-based emergency medical services agency

Opioid abuse is a growing and significant public health concern in the United States. Naloxone is an opioid antagonist that can rapidly reverse the respiratory depression associated with opioid toxicity. Georgetown University's collegiate-based emergency medical services (EMS) agency recently adopted a protocol, allowing providers to administer intranasal naloxone for patients with suspected opioid overdose. While normally not within the scope of practice of basic life support prehospital agencies, the recognition of an increasing epidemic of opioid abuse has led many states, including the District of Columbia, to expand access to naloxone for prehospital providers of all levels of training. In particular, intranasal naloxone is a method of administering this medication that potentially avoids needlestick injuries among EMS providers. Universities with collegiate-based EMS agencies are well positioned to provide life-saving treatments for patients acutely ill from opioid overdose.     

Sufficiency Revisited: Rethinking Statistical Algorithms in the Big Data Era

The big data era demands new statistical analysis paradigms, since traditional methods often break down when datasets are too large to fit on a single desktop computer. Divide and Recombine (D&R) is becoming a popular approach for big data analysis, where results are combined over subanalyses performed in separate data subsets. In this article, we consider situations where unit record data cannot be made available by data custodians due to privacy concerns, and explore the concept of statistical sufficiency and summary statistics for model fitting. The resulting approach represents a type of D&R strategy, which we refer to as summary statistics D&R; as opposed to the standard approach, which we refer to as horizontal D&R. We demonstrate the concept via an extended Gamma–Poisson model, where summary statistics are extracted from different databases and incorporated directly into the fitting algorithm without having to combine unit record data. By exploiting the natural hierarchy of data, our approach has major benefits in terms of privacy protection. Incorporating the proposed modelling framework into data extraction tools such as TableBuilder by the Australian Bureau of Statistics allows for potential analysis at a finer geographical level, which we illustrate with a multilevel analysis of the Australian unemployment data. Supplementary materials for this article are available online.     

ANALYZING MODELS WITH MULTIPLE-OUTCOME VARIABLES *

Multivariate designs have been useful in testing models with more than one output variable. This paper explains the use of the step-down F statistic, a technique that allows a more refined analysis than does the traditional multivariate or univariate F test by examining sequential interactions among dependent variables in a multiple-response set. An illustration is presented within the context of a laboratory experiment designed to examine a manipulation effect on a three-variable causal chain. The example illustrates the misleading interpretation that could result without the information provided by the step-down statistic.