Data like any other? Sexual and reproductive health, Big Data and the Sustainable Development Goals

Author:

Hammond Natalie1ORCID,Moretti Angelo2

Affiliation:

1. Department of Social Care and Social Work, Manchester Metropolitan University, Manchester, UK

2. Department of Methodology and Statistics, Faculty of Behavioural Sciences, Utrecht University, Utrecht, Netherlands

Abstract

This article examines the possibilities and pitfalls of using Big Data to address sexual and reproductive health concerns as related to the Sustainable Development Goals (SDGs), paying particular attention to contextual difference in development settings. The global datafication of sexual and reproductive life has taken place at great speed. However, evidential deficiencies and a lack of critical engagement of the specific issues around working with sexual and reproductive health Big Data in development contexts is apparent. Informed by critical data studies, and framed by a political economy perspective which calls attention to power structures, we seek to deepen our understanding of the role and challenges that Big Data around sexual and reproductive health in the Low and Middle-Income Countries can play in addressing the SDGs. First, we explore the ways in which sexual datafication processes produce Big Data. We then consider how such Big Data could directly contribute to addressing the SDGs beyond simply monitoring and evaluating. Next, we unpick how the sensitive and stigmatised nature of sexual and reproductive health can have ramifications in data-driven contexts where significant power asymmetries exist. By doing so, we provide a more nuanced articulation of the challenges of datafication by contextualising the stigma around sexual and reproductive in a datafied context. We argue that whilst Big Data in relation to sexual and reproductive health shows potential to support the SDGs, there are specificities that must be considered to ensure that the push for data-driven approaches does no harm.

Publisher

SAGE Publications

Subject

Anthropology,Gender Studies

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on the Application of Health Big Data based on Semi-Supervised Learning Algorithm;2024 3rd International Conference for Innovation in Technology (INOCON);2024-03-01

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