The Solidary Relationship’s Consequences for the Ebb and Flow of Activism: Collaborative Evidence from Life-History Interviews and Social Media Event Analysis,

Acting in solidarity with deprived others has become a central topic in social movement research. The explanations of solidarity activism or political altruism are few. However, social movement researchers have claimed that solidarity with out-of-group others is a by-product of in-group interaction. In contrast, we argue that out-group interaction with the deprived other and the formation of a solidary relationship is central to the ebb and flow of solidarity activism. We investigate the Danish refugee solidarity movement and show that the meeting with the deprived other 1) brings about an interaction order which makes an ethical demand on the activists to care for the other both within the bounds of the situations and in the future; 2) enacts and amplifies activists’ values and beliefs because the deprived other becomes an exemplar of the injustice and the need to help the broader group of people in the same fragile situation. We develop and test this theory drawing on 42 life-history interviews and a social media dataset containing a panel of 87,455 activists participating in refugee solidarity groups.     

Max‐infinitely divisible models and inference for spatial extremes

For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max‐stable models are inadequate to capture the rate of joint tail decay, and to estimate joint extremal probabilities beyond observed levels. We here develop a more flexible modeling framework based on the class of max‐infinitely divisible processes, which extend max‐stable processes while retaining dependence properties that are natural for maxima. We propose two parametric constructions for max‐infinitely divisible models, which relax the max‐stability property but remain close to some popular max‐stable models obtained as special cases. The first model considers maxima over a finite, random number of independent observations, while the second model generalizes the spectral representation of max‐stable processes. Inference is performed using a pairwise likelihood. We illustrate the benefits of our new modeling framework on Dutch wind gust maxima calculated over different time units. Results strongly suggest that our proposed models outperform other natural models, such as the Student‐t copula process and its max‐stable limit, even for large block sizes.     

Health Component of Inequalities Associated with Income Mobility Over the Life Cycle

Social Indicators Research - From the two-wave French Health and Professional Career survey in 2006 and 2010, the income distribution associated with income mobility between these two dates shows...     

Inequality in Interaction: Equalising the Helper–Recipient Relationship in the Refugee Solidarity Movement

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - In this paper, we supplement existing scholarship on the interactional process within volunteering with one that focuses...     

Exploring Cultural Issues for Constellation Work in South Africa

Constellation work is a therapeutic and counselling intervention recognised in Germany and other European countries since the 1970s. Various scientists and practitioners have contributed to its theoretical and practical development, and research on the subject has increased over the past few years. However culture in constellation work has received little research attention and has not been empirically studied in African contexts. The aim of this article is to reflect on culture and its influence on constellation work in multicultural, post‐apartheid South Africa. An empirical qualitative research approach within the phenomenological paradigm was adopted. Six constellation facilitators were interviewed with in‐depth and field notes taken during participative observations of constellation workshops. The findings provide insight into culture in constellation work in the South African context. Theoretical and practical recommendations for scientists and therapy practitioners working with systemic interventions like constellation work are provided.     

Measuring the drivers of gender inequality and their impact on development: the role of discriminatory social institutions

This paper highlights the key role of discriminatory social institutions – formal and informal laws, social norms, and practices – as the underlying drivers of gender inequality. Using the Social Institutions and Gender Index (SIGI) from the OECD Development Centre, this paper assesses the cost of gender-based discrimination in social institutions for economic and human development. Quantifying such complex issues is a powerful lever for advocacy, where rights-based arguments have tended to gain less traction. The paper provides evidence that measuring the invisible is feasible and critical to position social norms on the policy radar. It demonstrates that any truly transformative post-2015 development agenda must take into account how such inequalities impact the development pathways of women and girls across their entire life course, limiting their rights and empowerment opportunities.     

Using repeated-prevalence data in multi-state modeling of renal replacement therapy

Multi-state models help predict future numbers of patients requiring specific treatments but these models require exhaustive incidence data. Deriving reliable predictions from repeated-prevalence data would be helpful. A new method to model the number of patients that switch between therapeutic modalities using repeated-prevalence data is presented and illustrated. The parameters and goodness of fit obtained with the new method and repeated-prevalence data were compared to those obtained with the classical method and incidence data. The multi-state model parameters’ confidence intervals obtained with annually collected repeated-prevalence data were wider than those obtained with incidence data and six out of nine pairs of confidence intervals did not overlap. However, most parameters were of the same order of magnitude and the predicted patient distributions among various renal replacement therapies were similar regardless of the type of data used. In the absence of incidence data, a multi-state model can still be successfully built with annually collected repeated-prevalence data to predict the numbers of patients requiring specific treatments. This modeling technique can be extended to other chronic diseases.     

Adaptive Warped Kernel Estimators

In this work, we develop a method of adaptive non‐parametric estimation, based on ‘warped’ kernels. The aim is to estimate a real‐valued function s from a sample of random couples (X,Y). We deal with transformed data (Φ(X),Y), with Φ a one‐to‐one function, to build a collection of kernel estimators. The data‐driven bandwidth selection is performed with a method inspired by Goldenshluger and Lepski (Ann. Statist., 39, 2011, 1608). The method permits to handle various problems such as additive and multiplicative regression, conditional density estimation, hazard rate estimation based on randomly right‐censored data, and cumulative distribution function estimation from current‐status data. The interest is threefold. First, the squared‐bias/variance trade‐off is automatically realized. Next, non‐asymptotic risk bounds are derived. Lastly, the estimator is easily computed, thanks to its simple expression: a short simulation study is presented.