Young people’s perceptions of power and influence as a basis for understanding contemporary citizenship

Persistent simplistic binary discourses of young people’s citizenship portray them either as civically deficit and disengaged citizens or the creators of new democratic modes and approaches. This paper draws on field research with two groups of young people in Australia to better recognise the nuance of young people’s experiences of citizenship, power and influence. The study investigated the extent to which different groups of young people believe that they have the power to influence society; the ways in which they seek this influence; the current barriers to their influence; and what would enable them to have greater influence. Our analysis in this paper draws on Lukes’ concepts of power [2005. Power: A Radical View. 2nd ed. London: Palgrave Macmillan] and Arvanitakis’ framework of citizenship engagement and empowerment [in Arvanitakis, J., and E. Sidoti. 2011. “The Politics of Change: Where to for Young People and Politics.” In Their Own Hands: Can Young People Change Australia?, edited by L. Walsh and R. Black, 11–20. Melbourne: ACER Press], but also builds on an emerging scholarship concerned with the geographic dimensions of young people’s citizenship engagement and action, as well as with the affective, relational and temporal dimensions of this engagement and action. Our findings suggest that power works in different ways to both constrain and liberate young people as citizens – sometimes at the same time. The paper concludes with an argument for the continuing need to understand young people’s lived and located experiences of engagement, power and influence in more nuanced and sophisticated ways. This includes reframing the discussion about young people’s experiences in terms of the nature of their democratic engagement and action rather than simply their citizenship.     

A CANONICAL ANALYSIS OF MANAGERIAL-ENVIRONMENTAL RELATIONSHIPS: IMPLICATIONS FOR METHODOLOGY AND POLICY*

The present study uses canonical analysis to examine the contingency model of organizations in the nursing home field. Data on environmental pressures and managerial practices relevant to the decision-making process are analyzed. Results support the theory that managerial practices are contingent on environmental pressures. The implications of these results for health-care decision makers and for future assessments of managerial-environmental relationships are discussed.     

Discretionary Use of Computers: An Empirically Derived Explanatory Model*

This study identifies variables that explain variations in computer use. Factor analysis of data gathered from 422 business administration faculty reveal eight themes among the independent variables. Seven of these factors significantly discriminate among non, minimal, and high users. These results suggest an empirical model for future studies and provide policy insights for decision makers seeking to stimulate computer usage. Additionally, the study shows that there is much commonality between the previously separate organizational innovation and information systems implementation streams. It also demonstrates that motivation theory may be a valid framework within which to study computer use.     

Relationship education research: current status and future directions

The overarching aim of this article is to review the research on relationship education programs and approaches that has been published or accepted for publication since the last review article in 2003. This article provides a critical overview of the relationship education field and sets an agenda for research and practice for the next decade. A theme weaved throughout the article is the ways in which relationship education is similar and different from couples therapy, and we conclude that there can be a synergistic, healthy marriage between the two. We then provide recommendations for future directions for research in the relationship education field. Finally, the coauthors comment on our experiences in both the relationship education field and the couples therapy field as both researchers and interventionists.     

Pension policy in China, Singapore, and South Korea: An assessment of the potential value of the notional defined contribution model

The rate of population aging is increasing in the developing world and the trend is particularly dramatic in East Asia. One consequence is sharp increases in old-age dependency ratios which have major implications for the sustainability of current public pension schemes. These trends are pushing pension policy experts in many of these countries to search for new pension models that are more suited to the increased demographic pressures they will be facing in the decades ahead. In this article we discuss five alternative public pension models with a focus on the newest of these models, the notional defined contribution (NDC) approach. We consider three countries with very different pension systems in place, two from East Asia (China and South Korea) and one from South East Asia (Singapore). The central question we address is which (if any) of the limitations in these existing models might more adequately be addressed using a variant of the NDC model. We conclude that the NDC model has the most to offer China and the least to offer Singapore.     

Shrinkage inverse regression estimation for model-free variable selection

Summary.  The family of inverse regression estimators that was recently proposed by Cook and Ni has proven effective in dimension reduction by transforming the high dimensional predictor vector to its low dimensional projections. We propose a general shrinkage estimation strategy for the entire inverse regression estimation family that is capable of simultaneous dimension reduction and variable selection. We demonstrate that the new estimators achieve consistency in variable selection without requiring any traditional model, meanwhile retaining the root n estimation consistency of the dimension reduction basis. We also show the effectiveness of the new estimators through both simulation and real data analysis.