‘Bringing coals to Newcastle’? Human rights,civil rights and social movements in New York City

In this article we examine the encounter between global human rights ideas and domestic discourses of civil rights and social justice, focusing on processes of translation and adaptation of women's human rights in two ethnographic sites in New York City. The first site is a citywide coalition working for the adoption of a New York City human rights ordinance. The second site is an advocacy organization working on domestic violence issues. We find that the local adoption of human rights in New York City – the ‘domestication’ of human rights – takes place in two central sites: law and social movement. We further find that the process of translation takes place unevenly in the two sites, and it is driven primarily by the actors, mechanisms and technologies in the social movement arena. Overall, we witness the emergence of a domestic human rights movement as a new counter‐hegemonic space, characterized by multiplicity in meanings, ideological heterogeneity and ambivalence from those engaged in its construction.     

Approximation of the Distribution of the Location Parameter in the Growth Curve Model

Abstract.  In this paper an Edgeworth-type approximation of order O(n ⁻² ) to the density of the estimator of the location parameter in the growth curve model has been derived. The approximation is a mixture of a normal and a Kotz-type distribution, thus being an elliptical distribution. A condition for unimodality of the mixture was found and marginal distribution of a subvector of the mixture distribution was derived. Finally, a small example was given to demonstrate an application of the approximation.     

Residuals in the Extended Growth Curve Model

Abstract.  The Extended Growth Curve model is considered. It turns out that the estimated mean of the model is the projection of the observations on the space generated by the design matrices which turns out to be the sum of two tensor product spaces. The orthogonal complement of this space is decomposed into four orthogonal spaces and residuals are defined by projecting the observation matrix on the resulting components. The residuals are interpreted and some remarks are given as to why we should not use ordinary residuals, what kind of information our residuals give and how this information might be used to validate model assumptions and detect outliers and influential observations. It is shown that the residuals are symmetrically distributed around zero and are uncorrelated with each other. The covariance between the residuals and the estimated model as well as the dispersion matrices for the residuals are also given.