Reproducing (Historical) Structural Injustice: On and Beyond Alasia Nuti’s Injustice and the Reproduction of History: Structural Inequalities, Gender and Redress

Author(s):  
Jennifer M. Page
Author(s):  
Alasia Nuti

AbstractDemands calling for reparations for historical injustices—injustices whose original victims and perpetrators are now dead—constitute an important component of contemporary struggles for social and transnational justice. Reparations are only one way in which the unjust past is salient in contemporary politics. In my book, Injustice and the Reproduction of History: Structural Inequalities, Gender and Redress, I put forward a framework to conceptualise the normative significance of the unjust past. In this article, I will engage with the insightful comments and try to address the concerns of the contributors to the symposium on my book. I will discuss (i) whether and in what sense my framework incorporates past-regarding duties, (ii) how it is different from causal interpretations of the relationship between past and present injustice, (iii) whether it can carve out a greater place for blame in our thinking about responsibility for (historical) structural injustice, (iv) whether such a responsibility needs to hinge upon an account of solidarity, and (v) how de-temporalising injustice can cast new light on immigration politics. In particular, I will stress and further clarify the importance that the notion of ‘structural debt’, which my book develops to reflect on historical responsibility, can play in thinking about what is owed to an unjust history.


2021 ◽  
pp. 1-20
Author(s):  
Annette Zimmermann ◽  
Chad Lee-Stronach

Abstract It is becoming more common that the decision-makers in private and public institutions are predictive algorithmic systems, not humans. This article argues that relying on algorithmic systems is procedurally unjust in contexts involving background conditions of structural injustice. Under such nonideal conditions, algorithmic systems, if left to their own devices, cannot meet a necessary condition of procedural justice, because they fail to provide a sufficiently nuanced model of which cases count as relevantly similar. Resolving this problem requires deliberative capacities uniquely available to human agents. After exploring the limitations of existing formal algorithmic fairness strategies, the article argues that procedural justice requires that human agents relying wholly or in part on algorithmic systems proceed with caution: by avoiding doxastic negligence about algorithmic outputs, by exercising deliberative capacities when making similarity judgments, and by suspending belief and gathering additional information in light of higher-order uncertainty.


2021 ◽  
Vol 28 (1) ◽  
pp. 1-3
Author(s):  
Beth Ferholt ◽  
Ivana Guarrasi ◽  
Alfredo Jornet ◽  
Bonnie Nardi ◽  
Antti Rajala ◽  
...  

2021 ◽  
pp. 107780122110373
Author(s):  
Vania Smith-Oka ◽  
Sarah E. Rubin ◽  
Lydia Z. Dixon

This article, based on ethnographic research in Mexico and South Africa, presents two central arguments about obstetric violence: (a) structural inequalities across diverse global sites are primarily linked to gender and lead to similar patterns of obstetric violence, and (b) ethnography is a powerful method to give voice to women's stories. Connecting these two arguments is a temporal model to understand how women across the world come to expect, experience, and respond to obstetric violence—that is, before, during, and after the encounter. This temporal approach is a core feature of ethnography, which requires long-term immersion and attention to context.


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