Intersectionality in a Nutshell

1. Structural Intersectionality

In her analysis, Dr. Crenshaw notes that “structural intersectionality” refers to how social structures and institutions are often ill-equipped to address the compounded realities of those who occupy multiple marginalised identities. For example, she describes how women of color seeking shelter from domestic violence often face barriers not encountered by white women, such as language obstacles, immigration status issues, and the lack of culturally responsive services. These structural deficiencies mean that “the needs of women who are at the intersection of race and gender often go unmet.”

Relation to Data Governance in Africa

Across the continent, digital ID systems are presented as gateways to modern life. They promise legal recognition, the ability to authenticate oneself, access to government services, and participation in the formal economy. Kenya and Nigeria, for example, have embraced universal registration and have goals to enrol every resident, including children, into national digital ID systems.³ In theory this supports more efficient service delivery and better planning. Yet this promise relies on a fragile assumption that people already possess, or can easily obtain, the documents required to enrol in the first place.

According to Research ICT Africa, a significant number of rural and low-income households do not have primary registration documents, particularly birth certificates and other foundational papers essential for digital ID enrolment. For those without documents, an alternative pathway sometimes exists, such as travelling to a central office to swear an affidavit. This option tends to work for undocumented individuals who are mobile and can afford the trip. For people with limited mobility, some systems offer a flexible arrangement where a documented relative is allowed to complete parts of the registration process on their behalf. This approach supports disabled citizens who already possess the paperwork needed to authenticate a family link.

Consider an individual who is both without proper documentation and living with reduced mobility, or someone living with two intersecting identities that exacerbate their state of marginalisation. Neither alternative is ideal for them. They likely cannot travel to the capital to swear an affidavit due to prohibitive costs, and they cannot designate a relative because their entire household lacks formal papers. These two disadvantages reinforce one another. The remedy for undocumented residents assumes physical mobility, while the remedy for residents with disabilities assumes the presence of documented kin. Without enrollment this individual is now excluded from datasets used to plan services, distribute social protection, and expand connectivity.

2. Political Intersectionality

Dr. Crenshaw describes how political intersectionality refers to how women of color are rendered invisible when the advocacy agendas of groups they belong to, such as anti-racist movements and feminist movements, treat race and gender as mutually exclusive terrains. This forces individuals to split their political energies between sometimes opposing agendas, where the “raced” experience is defined by men of color and the “gendered” experience is defined by white women. For instance, activists and the LAPD were reluctant to release domestic violence statistics by precinct because of conflicting political fears. Anti-racist advocates feared the data would reinforce stereotypes of minority communities as “pathologically violent,” while feminist advocates worried it would allow society to dismiss domestic violence as merely a “minority problem” rather than a systemic issue affecting all women. In the end, the strategic silence of both movements effectively erased the specific needs of women of color who were actually experiencing the violence.

Relation to Data Governance in Africa

In today’s data governance landscape in Africa, this could manifest as a direct conflict between Digital Rights and Gender Safety movements. A Digital Rights movement would likely prioritise total anonymity and encryption to protect activists from state surveillance. Simultaneously, a Gender Safety movement might advocate for real-name verification to combat online gender-based violence. For a queer woman activist in a repressive state, neither movement fully addresses her reality; she requires safety from both state persecution and identity-based harassment. Because these agendas push in opposite directions, her specific need for safe, anonymous participation is marginalised by both.

3. 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.⁴

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.

The Erasure at the Intersection

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.

The Resulting Data Failure

The result is that this woman appears in neither dataset. The religious intolerance data concludes that the community is under attack only from the outside, while the gender data claims to track national abuse rates but misses her entirely because she never stepped foot in a mainstream center. The data governance system has failed to create a “representation” for a woman whose silence is enforced by the need to protect her community from further stigmatisation. Moreover, by failing to capture her intersectional reality, the data governance system perceives no “demand” for the specific services she needs, such as culturally appropriate shelters or safe reporting channels, effectively rendering her crisis financially and politically invisible.