An exploratory study of acculturation among Muslims in Australia

Muslims constitute 2.2% of the Australian population. Given the current socio-political climate and the limited research, the present exploratory study explores the relationship between acculturation, ethnic identity, self-identity, generational status, religiosity, and demographics among adult Australian Muslims.

A cross-sectional convenience sample of 324 adult Australian Muslims completed either online or paper-based questionnaires in either English or Arabic. Recruitment was via convenience sampling and social media advertisements. Acculturation, ethnic identity (MEIM), religiosity, and demographic variables were measured.

The study sample was young and mostly female, with high religiosity levels. Acculturation was negatively correlated with ethnic identity. From multiple regression analysis, acculturation was predicted independently by religiosity (low), age (young), gender (male) and ethnic identity (low).

First generation Australian Muslims were older, had stronger ethnic identity and religiosity, and more commonly self-identified as non-Australian. By contrast second- and third-generation were more likely to self-identify as bicultural or Australian.

In summary, acculturation of Australian Muslims is influenced by multiple variables, particularly ethnic identity, religiosity, and generation; hence all these variables need to be included in policy regarding successful integration of migrants.     

Black men teaching: toward a theory of social isolation in organizations

ABSTRACT

While there continues to be increasing research about Black male teachers’ school-based experiences, there is less empirical evidence on the variation in these experiences for this subgroup. Drawing on Kanter’s Theory of Numbers and Group Composition, the researcher used the qualitative method to compare the perceptions of Black male teachers in schools that employ just one Black male teacher versus schools with larger numbers of Black male teachers. A theory of social isolation in organizations is proposed to explain differences in the variation of school-based experiences for Black male teachers. When compared to Black men in schools with larger percentages of Black male teachers on the faculty, those Black men who were the only Black male teachers on their faculty were more likely to describe feeling socially isolated and disconnected from their colleagues.     

Shadow Insurance

Life insurers use reinsurance to move liabilities from regulated and rated companies that sell policies to shadow reinsurers, which are less regulated and unrated off‐balance‐sheet entities within the same insurance group. U.S. life insurance and annuity liabilities ceded to shadow reinsurers grew from $11 billion in 2002 to $364 billion in 2012. Life insurers using shadow insurance, which capture half of the market share, ceded 25 cents of every dollar insured to shadow reinsurers in 2012, up from 2 cents in 2002. By relaxing capital requirements, shadow insurance could reduce the marginal cost of issuing policies and thereby improve retail market efficiency. However, shadow insurance could also reduce risk‐based capital and increase expected loss for the industry. We model and quantify these effects based on publicly available data and plausible assumptions.     

Inference on Causal Effects in a Generalized Regression Kink Design

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. We characterize a broad class of models in which a sharp “Regression Kink Design” (RKD or RK Design) identifies a readily interpretable treatment‐on‐the‐treated parameter (Florens, Heckman, Meghir, and Vytlacil (2008)). We also introduce a “fuzzy regression kink design” generalization that allows for omitted variables in the assignment rule, noncompliance, and certain types of measurement errors in the observed values of the assignment variable and the policy variable. Our identifying assumptions give rise to testable restrictions on the distributions of the assignment variable and predetermined covariates around the kink point, similar to the restrictions delivered by Lee (2008) for the regression discontinuity design. Using a kink in the unemployment benefit formula, we apply a fuzzy RKD to empirically estimate the effect of benefit rates on unemployment durations in Austria.     

Further Beyond the Basic Background Check: Predicting Future Unethical Behavior

In this paper, we analyze the ethical issues of using honesty and integrity tests in employment screening. Our focus will be on the United States context: legal requirements related to applicant privacy differ in other countries, but we posit that our proposed balancing test is broadly applicable. We start by discussing why companies have ethical and legal obligations, based on a stakeholder analysis, to assess the integrity of potential employees. We then move to a consideration of how companies currently use background checks as a pre‐employment screening tool, noting their limitations. We then take up honesty and integrity testing, focusing particularly on the problems of false positives and due process. We offer a balancing test for the use of honesty and integrity testing that takes in three factors: (1) the potential harm posed by a dishonest employee in a particular job, (2) the linkage between the test and the assessment process, and (3) the accuracy and validity of the honesty and integrity test. We conclude with implications for practice and future research.     

Mini-batch learning of exponential family finite mixture models

Mini-batch algorithms have become increasingly popular due to the requirement for solving optimization problems, based on large-scale data sets. Using an existing online expectation–maximization (EM) algorithm framework, we demonstrate how mini-batch (MB) algorithms may be constructed, and propose a scheme for the stochastic stabilization of the constructed mini-batch algorithms. Theoretical results regarding the convergence of the mini-batch EM algorithms are presented. We then demonstrate how the mini-batch framework may be applied to conduct maximum likelihood (ML) estimation of mixtures of exponential family distributions, with emphasis on ML estimation for mixtures of normal distributions. Via a simulation study, we demonstrate that the mini-batch algorithm for mixtures of normal distributions can outperform the standard EM algorithm. Further evidence of the performance of the mini-batch framework is provided via an application to the famous MNIST data set.     

Network Embeddedness in Exploration and Exploitation of Joint R&D Projects: A Structural Approach

This paper analyses how network embeddedness affects the exploration and exploitation of R&D project performance. By developing joint projects, partners and projects are linked to one another and form a network that generates social capital. We examine how the location, which determines the access to information and knowledge within a network of relationships, affects the performance of projects. We consider this question in the setup of exploration and exploitation projects, using a database built from an EU framework. We find that each of the structural embeddedness dimensions (degree, betweenness and eigenvector centrality) have a different impact on the exploration and exploitation project performance. Our empirical analysis extends to project management literature and social capital theory, by including the effect that the acquisition of external knowledge has on the performance of the project.     

Servant Leadership in the Public Sector: Employee Perspective

Public Organization Review - The purpose of this study is to explore how servant leadership affects public sector employee engagement, organisational ethical climate, and public sector reform, of...