Data systems are the backbone of public services in many African countries, but using one-dimensional categories (like “woman” or “youth”) creates the Identity Trap, failing to account for the multiple, compounding factors that affect people’s lives.
To reflect this real-world complexity and mitigate new risks, developing data governance frameworks through an intersectionality lens is essential.
What is Intersectionality?
Definition
in·ter·sec·tion·al·i·ty /ˌin.tə.sɛk.ʃəˈnæl.ə.ti/ (noun)
Intersectionality is an intellectual framework for understanding how various aspects of individual identity, including race, gender, social class, and sexuality, interact to create unique experiences of privilege or oppression
Rather than treating social categories separately, intersectionality looks at how they combine to create unique forms of exclusion or harm.
— Kimberlé Crenshaw
Origin
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Intersectionality is a framework focused on power, systems, and structures, explaining how institutions fail to include or protect individuals living at the crossroads of multiple forms of disadvantage. Building on Dr. Crenshaw’s analysis, it helps actors understand how factors like gender, location, and legal status combine to shape how people are affected by data policies and systems.
To analyse this interaction, Dr. Crenshaw identified three dimensions structural, political, and representational which highlight how exclusion occurs even when policies appear neutral.
Dimensions of Intersectionality
Representational Intersectionality
Representational intersectionality exposes how public stories, images, and “common sense” narratives can erase the challenges of people who sit at the crossroads of different facets of their identity, like race and gender, even when those involved claim to be fighting injustice. Dr. Crenshaw explored this phenomenon by briefly analysing the public response to the Central Park jogger case, mentioning that when feminists framed the case as “violence against women,” meanwhile, the “woman” they implicitly centered was white, therefore leaving the experiences of Black women who face sexual violence as an afterthought.
As it pertains to race, when antiracist advocates focused on the overpolicing of Black men, gender violence was sidelined. This meant the specific vulnerabilities of Black women to both racism and sexism were treated as a secondary challenge, if at all. Their experiences of sexual violence are not represented by the “generic woman,” nor are their experiences of racism represented by the “generic Black victim.” The role of representational intersectionality is to capture this erasure and illustrate how public narratives, when built on narrow representations, reinforce the very power dynamics they claim to challenge.
Relation to Data Governance in Africa
The “Religious Minority” vs. The “Gender-Based Violence” Narrative
Consider the case of a predominantly Christian African nation where the government and NGOs are collecting data to address two pressing human rights issues: religious intolerance and violence against women. The problem, however, is that the data collection is built on two standard, “default” storylines about what a victim looks like.
- The “Religious Persecution” narrative focuses on how the minority Muslim community is targeted by state security forces. Here, the data tells a story of public discrimination, constructing a “default victim” who is male, a man profiled at checkpoints, detained without cause, or denied jobs due to traditional attire.
- Running parallel to this is the “Gender-Based Violence” (GBV) narrative. This story focuses on domestic abuse and sexual assault, utilizing data from police stations and church-based support groups. Consequently, the “default victim” represented in this data is a Christian woman from the majority demographic who feels safe accessing these mainstream institutions.
Caught between these two scripts is the Muslim woman facing domestic violence. She is erased by the Religious Intolerance narrative because her suffering happens inside the home and because the data focuses on external persecution of the community (mostly targeting men). Simultaneously, she is erased by the Gender narrative because the data relies on reporting channels she does not feel safe using.
She may fear that reporting her husband to a predominantly Christian police force will bring shame to her minority community or fuel the stereotype that Muslim men are violent. Furthermore, because the “generic woman” in the public imagination is Christian, mainstream shelters may fall short in offering culturally appropriate care, such as halal food, prayer spaces, or female-only staff, effectively barring her entry.
Intersectionality and the Inclusive Data Charter
While understanding intersectionality as a theoretical framework is important, the next step is translating it into actionable policy. To operationalise these concepts, the international development community has turned to frameworks that explicitly link data practices with equity. Foremost among these is The Inclusive Data Charter (IDC), a global initiative coordinated by the Global Partnership for Sustainable Development Data which calls for data systems and practices that will \”account for disparities and be designed for the protection and empowerment of the most vulnerable people in society.\” This principle is indispensable in an era where policy and public services are increasingly data-driven, and where the risk of leaving people behind is greatest for those with overlapping, marginalised identities.
Intersectionality provides a practical framework for realising the IDC\’s vision. It equips decision makers, regulators, and civil society with the proper ideology to design data governance systems that move beyond one-size-fits-all approaches and transition to those that better reflect the complex realities of everyday people. Nevertheless, global charters like the IDC require adaptation to local contexts to achieve meaningful results. Universal standards frequently encounter specific barriers when applied to diverse geopolitical landscapes. Consequently, the next section shifts focus to African data governance, exploring how historical legacies and current technological realities demand a customised, intersectional strategy.