Since the carceral elements of #MeToo were first observed, long-simmering debates around what it means to listen to – and indeed believe – survivors have been reignited within Anglophone feminist anti-violence work and scholarship. Using analysis of the anger that erupts on social media when seemingly carceral feminist campaigns proclaim to be ‘led by’ survivors as a starting point, this article demonstrates that – while seemingly divided – much feminist work around sexual violence is deeply affected by a ‘survivor-led’ politics. Through situating this politics within feminism's testimonial legacies, I engage with citationally dominant texts to show that belief and listening – core principles of feminist work – have become increasingly ensnared with affective notions of innocence. The result is the production of work that is unable – or unwilling – to ask critical questions of survivor speech, and the circulation of a powerful core narrative: that because some survivors say they desire carceral outcomes, these can never be abandoned. Through asking questions around what it means to listen to, believe and respond to those who say they want carceral outcomes, I provide a thorough interrogation of the ethics and risks of the epistemological politics of being ‘survivor led’. Contending that a ‘survivor-led’ politics arises due to the affective force of a newly conceptualised figure – the figure of the wounded survivor – I argue that this politics risks furthering injustice for survivors everywhere, especially those who are deemed less ‘innocent’. I conclude by attending to the potential that lies instead in a ‘survivor-centred’ politics. Through offering compelling evidence of this politics in practice, I show the ways in which it encourages a different kind of listening and responding to survivors, and in turn a more just approach to justice seeking.
Building similarity graph...
Analyzing shared references across papers
Loading...
Molly Ackhurst
University of Greenwich
Feminist Theory
University of Greenwich
Building similarity graph...
Analyzing shared references across papers
Loading...
Molly Ackhurst (Tue,) studied this question.
synapsesocial.com/papers/68f984011881b68f3b7ae40c — DOI: https://doi.org/10.1177/14647001251380418