The Black Equity Coalition (BEC), in collaboration with the City of Pittsburgh, hosted the third Community Data Justice Collaborative (CDJC) Workshop. The CDJC is bringing community voice into the City of Pittsburgh’s data governance practice. This workshop was the first of several that will result in the development of a “style guide” that data stewards and data workers at the City can use to develop data products that accurately reflect community identities and treat residents with respect. This workshop explored ways that maps and data have been used to stigmatize communities, and enabled participants to develop guidance for data workers.
Getting to Know Each Other: The Sticky Dot Survey & Dinner Conversations
The workshop began with a survey that made use of sticky dots and stickers to foster connection among attendees. This interactive exercise encouraged participants to share their understanding of how decisions are made about technology and data, their level of confidence in working with data, and reflect on the power they have over data and technology in their personal life and community.
During dinner, attendees engaged with the prompt: “Share a time when you were stigmatized.” These stories highlighted the real-life consequences of how they have personally faced stigma in their lives. One participant shared the judgment they face for using a parking pass without having a visible disability. A second member of the group spoke of the challenges they faced after transferring to a predominantly white school as a Black student. A third story shared by a participant highlighted the stereotypes she faced as a young mother.
Understanding Territorial Stigma Through Data
The workshop then moved into the topic of “territorial stigmatization.” Territorial stigma is defined as mechanisms through which some places are made to be inferior to others. Territorial stigma is a label imposed on places from the outside. It is a way of taking away power from people associated with a place. When places are “othered” through stigma, the people associated with them are harmed, social hierarchies are reinforced, and the structural causes of inequity are obscured. Territorial stigmatization is another method of institutionalizing and perpetuating racism, classism, colonialism, and xenophobia, along with discrimination based on religion, ethnicity, gender identity, and sexual orientation.
The impact of stigma on people can be severe. It defines how systems (like criminal justice, education, and social services) interact with people. It also defines how people in society interact with one another based on their connection to where their community fits into a spatial hierarchy. People connected to stigmatized places often are rendered powerless or invisible, and continuing to treat some places as persistently inferior legitimizes continued injustice, discrimination, and harm. Our goal for the workshop was to identify practices that data workers could use to prevent territorial stigmatization in their maps, visualizations, and other forms of communication.
In the workshop, participants started a conversation about stigma after viewing examples of some of the ways communities have been stigmatized using data. Participants then worked together to explore ways that data workers can stop stigmatizing communities in their work. Research suggests this can be done by making a connection to structural issues, contesting classification and hierarchies, and by showing how power works in different contexts.
Key reflections from participants included:
- Who Collects Data Matters: Participants emphasized the importance of recognizing who has the power to collect and interpret data. This shapes the narrative and can perpetuate unconscious biases.
- Historical Context: Examples demonstrated how data has historically been used to categorize and stigmatize communities, often for exploitative purposes.
- Language Shapes Perception: Discussions highlighted how language can add to stigmatization. Participants pointed out using a term like “bright spots” to highlight areas doing “well” carries an implication for other areas. People and organizations creating data visualizations need to be careful and intentional and ask: is there a better word to use to get to what I’m saying?
Moving Forward: Practices to Avoid Stigmatizing Communities
The workshop concluded with a robust discussion of steps data workers can take to prevent the stigmatization of communities. Suggestions included:
- Community-Led Data Collection: Ensure those collecting data reflect and are embedded in the community, fostering trust and more accurate representation.
- Intentional Language: Be mindful of the words used in reports and visualizations. Replace ambiguous or loaded terms with clear, value-neutral language.
- Accountability in Storytelling: Empower community members to tell their own stories rather than allowing outside narratives to dominate.
- Empathy in Data Work: Build relationships with the people behind the data, prioritize lived experiences, and commit to ongoing reflection and improvement.
As one participant put it: “There is no ‘unintentional’ when you’re talking about somebody’s life.” This sentiment underscores the responsibility we all share to handle data with care and to ensure it serves as a tool for equity rather than oppression.
Stay tuned for future workshops and initiatives as we continue to shape a more just and equitable future for all at: www.BlackEquityCoalition.org
About the Community Data Justice Collaborative (CDJC):
The Black Equity Coalition (BEC), in partnership with the City of Pittsburgh created the Community Data Justice Collaborative (CDJC) as part of the broader Data Justice for Pittsburgh’s Black Neighborhoods project, designed to empower Black residents with decision-making authority over how data is used, governed, and shared in the city. Pittsburgh is one of four U.S. cities selected for the Modern Anti-Racist Data Ecosystems (MADE) for Health Justice initiative, supported by the de Beaumont Foundation. The de Beaumont Foundation sponsored the BEC’s work to assist in accelerating the development of health-focused local data ecosystems that center principles of anti-racism, equity, justice, and community power.
The Community Data Justice Collaborative is a group of residents who engage in decisions that the City of Pittsburgh makes about data, technology, and policies that will serve as the foundation of the City’s emerging data governance process. The BEC will engage the Community Data Justice Collaborative and city data stewards in participatory activities to find agreement around how the city uses data and technology.
