Data Practice for a Politics of Care: Food Assistance as a Site of Careful Data Work

Title of the Paper

Data Practice for a Politics of Care: Food Assistance as a Site of Careful Data Work

Bibliographic Information

• Subject Area: Application of data practices and ethics of care in social services, particularly in the field of food assistance
• Keywords: Data, politics of measurement, care, digital citizenship, design

Research Background and Problem

• Identified Problems or Challenges:

  • Data has become a critical tool in civic decision-making, but data practices are not neutral; their production processes reflect power dynamics and cultural assumptions.
  • Mission-driven organizations face pressure to collect data to improve decision-making and enhance efficiency, but their limited resources and capacities lead to difficulties in data management.
  • A "Cycle of Disempowerment" exists in data practices, making it challenging for nonprofit organizations to leverage data-driven work to fulfill their missions.

• Significance:

  • As "datafication" continues to expand, data practices increasingly influence decision-making on social issues in both public and private domains.
  • In resource-constrained contexts, designing data practices that reflect organizational values can better serve communities rather than burden them with data collection.

• Research Motivation and Related Work:

  • Many nonprofits and municipal governments face challenges related to limited resources and data management, necessitating the design of ethical operational frameworks for social services.
  • Research in HCI (Human-Computer Interaction) has begun to explore the intersection of data, care perspectives, and civic engagement, but more empirical analysis is needed to understand how these practices manifest across different institutions.

Solution

• Method or Solution:

  • The authors conducted an 11-month field-based collaborative study, analyzing the data practices of a hybrid mission-driven organization's food distribution program.
  • The work focused on designing tools and processes that embody an "Ethic of Care," such as protecting vulnerable populations during data collection and reducing the burden of data collection.

• Innovative Aspects of the Solution:

  • Introduced the concept of "Careful Data Practice," emphasizing the core value of relationship management.
  • Explored how organizations integrate care ethics through technological means (e.g., survey design) and social practices (e.g., building community trust).
  • Used a multidimensional framework (e.g., "addressing unmet care needs") to analyze the systemic characteristics of data practices.

• Implementation Steps and Key Techniques:

  1. Selecting Data Measurement Content: Designed surveys to balance organizational goals with funder requirements while refusing to collect data that could put the community at risk (e.g., immigration status).
  2. Field Data Collection: Used mobile devices (iPads and smartphones) to record data while empowering community navigators with greater data collection authority to enhance resident trust.
  3. Data Usage:
     • Supporting funding applications.
     • Tracking individual cases to provide ongoing services and assistance.
     • Using data for policy advocacy to drive structural change.

Research Outcomes

• Specific Outcomes:

  • Documented and analyzed how a data practice system incorporating the "Ethic of Care" operates under the tension of resource constraints and multiple institutional logics.
  • Provided in-depth recommendations on designing social service data systems that reflect care ethics.

• Advantages:

  • Data practices not only focus on data efficiency but also emphasize human connections, trust, and community support.
  • Data practices avoid over-measurement, protect the privacy of vulnerable groups, and meet institutional funding needs.
  • Achieved technical and cultural adaptation through "patchwork data adjustments."

• Experimental or Evaluation Results:

  • Data practices were found to enhance the organization's ability to secure funding, support individual needs, and advocate for policy change.
  • The system adapted flexibly to community feedback to optimize data tools (e.g., replacing case numbers in surveys with phone numbers).

• Limitations and Future Directions:

  • Limitations: Did not fully address the inherent coloniality and data simplification issues in social systems (e.g., the impact of quantification on care practices).
  • Future Directions: Explore how data work can better reflect ethical care in cross-institutional collaborations; investigate additional tool designs to support the needs of resource-constrained organizations.

Design Recommendations

• Prioritize Inclusivity Over Usability: Provide more support for community members and workers from diverse linguistic backgrounds, even at the expense of user interface experience.
• Reduce Resource Consumption: Data systems should minimize the labor and time demands on resource-constrained organizations, for example, through lightweight tool designs.
• Resist Data Quantification: Data systems should allow flexibility and the option to decline answering sensitive questions while supporting qualitative interpretation and community context analysis.

This paper offers valuable practical experiences and theoretical support for applying data ethics and the concept of care in resource-limited local services, providing guidance for design and research in the intersection of technology and social services.