Spatial|Data Justice: Mapping and Digitised Strolling against Moral Police in Iran
Azadeh Akbari
Abstract
Through a case study of women’s resistance against the moral police in Iran, this paper contends that claims to data justice cannot be investigated unless they are situated in broader political frames. Whilst the current literature uses a single axis analysis of data justice as well as conceptual tools that are appropriated for democratic power relations, this research positions data justice in a matrix of injustices in an unequal and undemocratic political apparatus.
The paper scrutinises the intersection of data and spatial injustice in Iran by analysing the way traffic camera footage is used against female drivers with improper veiling. Considering compulsory hijab and policing of it as a spatial injustice that limits and disturbs women’s access to public places, the case study examines ways of resistance that address spatial|data injustice: firstly, a mobile phone application called Gershad that uses collective mapping to pin moral police patrols on maps by users; secondly, a social media campaign called White Wednesdays that encourages women to film and share their public strolls without hijab, their confrontations with religious pro-regime people, and videos of singing, dancing and cycling in public spaces.
Using Fraser’s theory of “abnormal justice”, this research draws attention to particularities of each case of data justice; taking into account the intersections of socio-political axes of injustice in different layers of local, regional and global analysis. The paper offers a “situated” analytical framework by bringing in space as an inquisitive component and moves from a sole discussion of data justice to a more intersectional study of spatial and data justice combined. Participation in “small data” projects is introduced as one resistance strategy against injustices of big data systems, fulfilling the principle of “parity of participation” to achieve justice, especially in undemocratic political contexts.
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