Variable selection in partial linear regression with functional covariate

The problem of variable selection is considered in high-dimensional partial linear regression under some model allowing for possibly functional variable. The procedure studied is that of nonconcave-penalized least squares. It is shown the existence of a √n/s_n-consistent estimator for the vector of p_n linear parameters in the model, even when p_n tends to ∞ as the sample size n increases (s_n denotes the number of influential variables). An oracle property is also obtained for the variable selection method, and the nonparametric rate of convergence is stated for the estimator of the nonlinear functional component of the model. Finally, a simulation study illustrates the finite sample size performance of our procedure.     

Adaptive wavelet estimation of a density from mixtures under multiplicative censoring

In this paper, a mixture model under multiplicative censoring is considered. We investigate the estimation of a component of the mixture (a density) from the observations. A new adaptive estimator based on wavelets and a hard thresholding rule is constructed for this problem. Under mild assumptions on the model, we study its asymptotic properties by determining an upper bound of the mean integrated squared error over a wide range of Besov balls. We prove that the obtained upper bound is sharp.     

‘Leave no one behind’ and the challenge of intersectionality: Christian Aid's experience of working with single and Dalit women in India

The principle of ‘leaving no one behind’ is strongly emerging as a defining aspect of the new development framework under negotiation in 2015. This stems from an acknowledgement of the failure of the Millennium Development Goals in securing benefits for the most marginalised groups, those suffering from economic deprivation and discrimination as a result of intersecting inequalities. As the new development framework takes shape, national-level experiences of tackling intersecting inequalities can provide lessons on the shifts required in policy and practice to address the specific needs of women experiencing deprivation, violence, and discrimination because of their gender and other identities. This case study illustrates lessons learnt from Christian Aid's programmatic experience in several states of India in support of Dalit women and single women as they individually and collectively struggle to gain dignity and realise their rights.     

Disability, social exclusion and the consequential experience of justiciable problems

In this article, we examine the situation of disabled people in England and Wales with regard to one specific aspect of social exclusion—experience of justiciable problems, and the potential effects such problems can have on their lives. Having defined 'disability', we examine how this fits within the wider dialogue on social exclusion issues. By analysing the results of the Legal Services Research Centre's (LSRC) periodic survey of justiciable problems, we find that disabled respondents were not only more likely to experience a problem, they also experienced more problems. Increased likelihood of a problem was observed in the majority of problem categories and particularly those relating to issues of social exclusion, such as housing and welfare benefits. This propensity to experience multiple problems can lead to a negative impact on the lives of long-term ill and disabled people.     

Corporate political power and US foreign policy, 1981–2002: the role of the policy-planning network

Theory and Society - Recent empirical work has offered strong support for ‘biased pluralism’ and ‘economic elite’ accounts of political power in the United States, according...     

Myths and Misconceptions About University Student Volunteering: Development and Perpetuation

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - This paper examines myths and misconceptions about university student volunteering. Our study explored the experiences of...     

Sustainable landscaping programs in the United States and their potential to encourage conservation and support ecosystem services

Sustainable landscaping programs are voluntary initiatives that recommend a set of practices to improve the environmental quality of urban ecosystems by providing landscaping materials, guidelines, and educational resources. Our goal was to examine the recommendations and outcomes of these programs in the United States and their value for encouraging conservation practices in residential ecosystems. We conducted a comprehensive web search and identified 193 sustainable landscaping programs in the United States. Programs aim to increase native species richness, affordably manage stormwater runoff, and offer residents meaningful experiences with nature. Sustainable landscaping programs present many opportunities to engage people with local ecological knowledge and conservation practices, provide accessible spaces for environmental education, cultivate interdisciplinary research collaborations, and advance inclusion in conservation. However, assessments of their ecological value are rare, leaving many questions surrounding the benefits to biodiversity and water quality afforded by participation. Many programs also require investments in landscaping materials and certification fees that might limit participation by some households. Future work should examine how recommended practices influence urban biodiversity, identify and address barriers to participation, and generate social-ecological knowledge that can inform future programs.

     

Growing the Volunteer Pool: Identifying Non-Volunteers Most Likely to Volunteer

There are ongoing management and societal challenges affecting volunteering participation. These place a premium on organizations identifying individuals that currently do not volunteer but have the willingness and capacity to do so, the “Potentials”. Supplementing the limited non-volunteer literature, we seek to quantify this potential volunteer pool using constructs aligned to the willingness, capability and availability dimensions from Meijs et al.’s (Volunt Action 8:36–54, 2006) volunteerability framework. Using binary logistic regression testing with a nationally representative sample of Australian volunteers and non-volunteers, we found partial support for the framework’s willingness and capability dimensions determining volunteer status. We then applied a predictive equation to the non-volunteer sample to calculate their percentage likelihood of volunteering, to identify a cohort of “Potential” volunteers. Further testing revealed statistically significant differences between this cohort compared to other non-volunteers based on various interventions for promoting volunteering. The implications of our novel study and an associated research agenda are discussed.