Looking Beyond ‘White Slavery’: Trafficking, the Jewish Association’s representation of ‘the potential victim’, and the dangerous politics of migration control in England, 1890-1910

This article seeks to revise Jo Doezema’s suggestion that ‘the white slave’ was the only dominant representation of ‘the trafficked woman’ used by early anti-trafficking advocates in Europe and the United States, and that discourses based on this figure of injured innocence are the only historical discourses that are able to shine light on contemporary anti-trafficking rhetoric. ‘The trafficked woman’ was a figure painted using many shades of grey in the past, with a number of injurious consequences, not only for trafficked persons but also for female labour migrants and migrant populations at large. In England, dominant organizational portrayals of ‘the trafficked woman’ had first acquired these shades by the 1890s, when trafficking started to proliferate amid mass migration from Continental Europe, and when controversy began to mount over the migration to the country of various groups of working-class foreigner. The article demonstrates these points by exploring the way in which the Jewish Association for the Protection of Girls and Women (JAPGW), one of the pillars of England’s early anti-trafficking movement, represented the female Jewish migrants it deemed at risk from being trafficked into sex work between 1890 and 1910. It argues that the JAPGW stigmatised these women, placing most of the onus for trafficking upon them and positioning them to a greater or a lesser extent as ‘undesirable and undeserving working-class foreigners’ who could never become respectable English women. It also contends that the JAPGW, in outlining what was wrong with certain female migrants, drew a line between ‘the migrant’ and respectable English society at large, and paradoxically endorsed the extension of the very ‘anti-alienist’ and Antisemitic prejudices that it strove to dispel.

Fast 2D/3D object representation with growing neural gas

This work presents the design of a real-time system to model visual objects with the use of self-organising networks. The architecture of the system addresses multiple computer vision tasks such as image segmentation, optimal parameter estimation and object representation. We first develop a framework for building non-rigid shapes using the growth mechanism of the self-organising maps, and then we define an optimal number of nodes without overfitting or underfitting the network based on the knowledge obtained from information-theoretic considerations. We present experimental results for hands and faces, and we quantitatively evaluate the matching capabilities of the proposed method with the topographic product. The proposed method is easily extensible to 3D objects, as it offers similar features for efficient mesh reconstruction.