On Not Reading Fifty Shades:Feminism and the Fantasy of Romantic Immunity

This paper explores the politics of feminist criticism of the Fifty Shades novels as seen in both traditional media commentary and popular online news and cultural websites and blogs. I argue that much media commentary, in broadsheet and other ‘respectable’ outlets particularly, has featured avowedly feminist writers dismissing the books as ‘bad’, not only containing bad writing and bad sex but, ultimately, as being bad for their women readers. Situating these responses within a history of feminist discomfort with popular erotic and romantic fiction marketed to women I read these responses as a form of ‘anti-romantic’ fantasy in which the reader/critic is able to assert both her immunity from the romantic fantasy offered in the text and her cultural distance from those women who are subject to it. Further, this act of disavowal is often linked to a professed concern for the women who read the novel who the critic argues will, inevitably, replicate the abusive and harmful relationship dynamics that the novel represent. Such a move then positions the feminist critic as not only more culturally intelligent than women readers of the novel but enacts a fantasy of respectable, middle-class feminist cultural custodianship. Such a fantasy, I argue, is connected to the post-feminist era in which we live, which has produced a class of self-appointed ‘feminist’ cultural critics who seek to contest their own cultural marginalisation through enacting a governmental authority to worry about other women. This paper, therefore, is a critical investigation of the pleasures and politics of very publicly not reading Fifty Shades and its significance for analysing the contemporary politics of popular culture and feminism.

A practical taxonomy of methods and literature for managing uncertain spatial data in geographic information systems

Perfect information is seldom available to man or machines due to uncertainties inherent in real world problems. Uncertainties in geographic information systems (GIS) stem from either vague/ambiguous or imprecise/inaccurate/incomplete information and it is necessary for GIS to develop tools and techniques to manage these uncertainties. There is a widespread agreement in the GIS community that although GIS has the potential to support a wide range of spatial data analysis problems, this potential is often hindered by the lack of consistency and uniformity. Uncertainties come in many shapes and forms, and processing uncertain spatial data requires a practical taxonomy to aid decision makers in choosing the most suitable data modeling and analysis method. In this paper, we: (1) review important developments in handling uncertainties when working with spatial data and GIS applications; (2) propose a taxonomy of models for dealing with uncertainties in GIS; and (3) identify current challenges and future research directions in spatial data analysis and GIS for managing uncertainties.