Thank God you're here: the coming generation and their role in future‐proofing Australia from the challenges of population ageing

Like much of the industrialised world, Australia's population is ageing, the implications of which are twofold: increasing demand for publicly funded services and a decline in the supply of prime working‐age people. In grappling with the challenges of a diminishing workforce, the Australian Government is currently relying on its migration programs to provide both the much‐needed labour and skills for the resource boom and also to stimulate the economy through population growth. However, there may be another, not yet fully considered solution to the upcoming demographic problem. This paper investigates how the grandchildren of the baby boomers, termed here the Thank God You're Here generation (Gen TGYH), might impact on Australia's predicted workforce shortage. This generation of workers will enter the labour force as the last of the baby boomers reach retirement age, and will not only be bigger in size than preceding generations (Y, X and Baby Boomers), but also potentially be better educated than the retiring generation. This paper will also canvas the opportunities for both Gen TGYH and employers as well as the challenges for policymakers and governments in maximising the opportunity provided by this generation in the Australian economy.     

Social Psychology,Consumer Culture and Neoliberal Political Economy

Consumer culture and neoliberal political economy are often viewed by social psychologists as topics reserved for anthropologists, economists, political scientists and sociologists. This paper takes an alternative view arguing that social psychology needs to better understand these two intertwined institutions as they can both challenge and provide a number of important insights into social psychological theories of self‐identity and their related concepts. These include personality traits, self‐esteem, social comparisons, self‐enhancement, impression management, self‐regulation and social identity. To illustrate, we examine how elements of consumer culture and neoliberal political economy intersect with social psychological concepts of self‐identity through three main topics: ‘the commodification of self‐identity’, ‘social categories, culture and power relations’ and the ‘governing of self‐regulating consumers’. In conclusion, we recommend a decommodified approach to research with the aim of producing social psychological knowledge that avoids becoming enmeshed with consumer culture and neoliberalism.     

The house of refuge movement: Humanitarian gesture or simple exploitation?

The 1800s marked the early development of a new approach to child welfare in the United States. Beginning with the house of refuge movement (1820s) and culminating with the creation of the juvenile court (1899), this developmental period has been traditionally praised as an age of humanitarian reform. Sociological research has suggested, however, that the creation of the juvenile court served mainly as a new form of social control designed to protect the power and privilege of the middle and upper classes while furthering the exploitation of the lower class. Unfortunately this research has treated only the reforms of the middle to late 1800s. The present study seeks to contribute to this literature by illuminating the early reforms. More specifically, an examination of the New York, Boston, and Philadelphia houses of refuge reveals that the exploitation thesis provides a more complete explanation of the emergence of these houses than does the humanitarian position.     

Leveraging the common and outsourcing the distinct: institutional difference and multinational company identity in emerging economies

ABSTRACT

This paper explores the challenges of outsidership faced by multinational companies (MNCs) accessing emerging economies. The paper departs from popular conceptualisations of culture drawing instead on social identity theory as part of an institutions-based view, to explain how employing a singularities approach can allow the identification of commonalities of Indianness and Australianness that can be leveraged to ameliorate negative socially embedded business norms that pose a challenge to MNC success in emerging economies. This study shows that despite recognised formal (regulatory) and informal (cultural) differences, managers of Australian MNCs operating in India were able to innovatively identify and exploit cultural commonalties/singularities to ease cultural adjustment and mitigate intergroup conflict, allowing them to achieve an innovative institutional fit. The paper discusses how, using this approach, sole-venture MNCs can access many of the benefits provided by collaborative entry modes while preserving MNC identity. We further propose that the singularities approach can provide a valuable starting point to develop culturally appropriate competence training initiatives.     

Model-based clustering with sparse covariance matrices

Statistics and Computing - Finite Gaussian mixture models are widely used for model-based clustering of continuous data. Nevertheless, since the number of model parameters scales quadratically with...     

Secrets and Lies: Involuntary Leakage in Deceptive Facial Expressions as a Function of Emotional Intensity

Darwin (1872) hypothesized that some facial muscle actions associated with emotion cannot be consciously inhibited, particularly when the to-be concealed emotion is strong. The present study investigated emotional “leakage” in deceptive facial expressions as a function of emotional intensity. Participants viewed low or high intensity disgusting, sad, frightening, and happy images, responding to each with a 5 s videotaped genuine or deceptive expression. Each 1/30 s frame of the 1,711 expressions (256,650 frames in total) was analyzed for the presence and duration of universal expressions. Results strongly supported the inhibition hypothesis. In general, emotional leakage lasted longer in both the upper and lower face during high-intensity masked, relative to low-intensity, masked expressions. High intensity emotion was more difficult to conceal than low intensity emotion during emotional neutralization, leading to a greater likelihood of emotional leakage in the upper face. The greatest and least amount of emotional leakage occurred during fearful and happiness expressions, respectively. Untrained observers were unable to discriminate real and false expressions above the level of chance.     

The Sociology of Inequality and the Rise of Neo-Inequality

Sociologists’ conventional approaches to understanding inequality and poverty do not adequately capture the causes, extent, and consequences of new forms of inequality that have emerged in the late 20th and early 21st centuries. Following a critique of conventional sociological theorizing on inequality and stratification, a synthesis of new sociological/social psychology thinking on inequality, and the use of case study data from Detroit, I explore, describe, and explain how neo-liberal ideology, neo-liberal systems of governance, and neo-liberal policies have created the neo-inequalities that now define our age.     

Mixture of latent trait analyzers for model-based clustering of categorical data

Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspondence between the estimated latent classes and groups in the population of interest. The mixture of latent trait analyzers model extends latent class analysis by assuming a model for the categorical response variables that depends on both a categorical latent class and a continuous latent trait variable; the discrete latent class accommodates group structure and the continuous latent trait accommodates dependence within these groups. Fitting the mixture of latent trait analyzers model is potentially difficult because the likelihood function involves an integral that cannot be evaluated analytically. We develop a variational approach for fitting the mixture of latent trait models and this provides an efficient model fitting strategy. The mixture of latent trait analyzers model is demonstrated on the analysis of data from the National Long Term Care Survey (NLTCS) and voting in the U.S. Congress. The model is shown to yield intuitive clustering results and it gives a much better fit than either latent class analysis or latent trait analysis alone.     

Discovering classes in microarray data using island counts

We present a new biclustering algorithm to simultaneously discover tissue classes and identify a set of genes that well-characterize these classes from DNA microarray data sets. We employ a combinatorial optimization approach where the object is to simultaneously identify an interesting set of genes and a partition of the array samples that optimizes a certain score based on a novel color island statistic. While this optimization problem is NP-complete in general, we are effectively able to solve problems of interest to optimality using a branch-and-bound algorithm. We have tested the algorithm on a 30 sample Cutaneous T-cell Lymphoma data set; it was able to almost perfectly discriminate short-term survivors from long-term survivors and normal controls. Another useful feature of our method is that can easily handle missing expression data.