FAIR Framework: Designing Equity Through Community Voices and Systems Thinking

The Fairness, Agency, Inclusion, Representation (FAIR) Framework is a systematic methodology that enables qualitative and quantitative research on structural factors--such as poverty, health, education and employment--that may drive inequality within communities. By focusing on the lived experiences of individuals within communities, FAIR enables researchers to identify and address issues that are often overlooked during the solution development process, such as representation, inclusion and agency.

What is FAIR?

FAIR specifically integrates community voices to identify and explore the architecture of disparities and the design of equity. This approach helps clarify the structural elements that lead to a community’s experience of inequity or adverse outcomes such as persistent poverty or health disparities. It can be applied to qualitative and quantitative research to capture factors impacting daily lives, and identify data, and models that would have otherwise remained unanticipated and hidden to those outside of the community. This approach also allows researchers to uncover unconscious biases and assumptions.

Being FAIR: "Nothing About Us Without Us"

Use of the FAIR Framework enables research that addresses: Fairness: Rooted in establishing a system that facilitates equity and overcomes disparities. Agency: Having the ability to exercise choice and to shape questions being asked, data being collected, models being built, results being interpreted, and actions being recommended. Inclusion: Creating a collaborative space for communities in the research endeavor and ensuring those being studied to define themselves apart from the aggregate population. Representation: Communities voicing their own realities as they live them. The research process can result in a narrative. That narrative needs to be shaped by a community’s voice that speaks for itself.

A group of coworkers discussing something while sitting in a circle

The FAIR Framework Addresses Complexity at its Source

Communities being modeled, like models themselves, comprise a unique combination of factors that can interact in complex ways. Those interactions may produce unanticipated disparities and outcomes. Community experts can help identify factors, and combinations of those factors, that may be evident only to those living in the communities themselves.

Including Voices of the Community is Crucial for Improving Data Integrity and Producing Equitable, Sustainable Solutions

Knowledge, beliefs, patterns, and expectations encapsulated within daily living and cultural norms can only be gleaned through community members themselves. In research, community voices uncover factors that literature reviews and data analysis may neither detect nor understand. Without taking time to listen and incorporate the lived experiences of those who will be affected by the question at hand, models may be theoretically accurate but realistically ineffective.