"The New Era of Tech-Enabled Traceability": Tensions between the FDA's Data Governance Vision and the Lived Realities of Food Producers

Technical Summary: "The New Era of Tech-Enabled Traceability": Tensions between the FDA's Data Governance Vision and the Lived Realities of Food Producers

Problem Statement
The U.S. Food and Drug Administration (FDA), under the Food Safety Modernization Act (FSMA), implemented the Food Traceability Rule, mandating that agri-food supply chain stakeholders maintain detailed, standardized tracking records for specific high-risk foods by January 2026. The FDA's vision is a "New Era of Tech-Enabled Traceability," where harmonized data serves as public health infrastructure to rapidly identify and remove contaminated food. However, the paper argues that this data-driven governance vision effectively reconfigures diverse stakeholders (farmers, fishers, processors, retailers) into "data workers." This reconfiguration imposes significant burdens that are often invisible in policy design, creating a disconnect between the abstract vision of efficiency and the lived realities of those required to perform the data work. The core problem is the misalignment between the Rule's standardized requirements and the varied infrastructural, cultural, and operational capacities of the stakeholders, leading to disproportionate burdens on smaller, under-resourced entities.

Methodology
The authors conducted a qualitative document analysis of 1,198 public comments submitted to Regulations.gov between 2014 and 2021 regarding the proposed Food Traceability Rule.

• Data Corpus: The dataset included typed text, PDF attachments, and combinations thereof from a diverse range of stakeholders, including farmers, fishers, industry associations, and consumers. The authors processed 1,337 files after filtering for broken or duplicate files.
• Theoretical Framework: The analysis was oriented by Data Feminism, specifically the first principle: "Examine Power." This lens treats public comments not merely as feedback but as active expressions of critique and resistance from marginalized positions, focusing on who bears the burden of compliance and whose voices are heard or erased.
• Analytical Process: The analysis proceeded in two phases:
  1. Open Coding: A bottom-up approach to identify recurring tensions between policy implementation and stakeholder realities (e.g., educational burdens, lack of technical options).
  2. Keyword-Driven Analysis: The authors searched for specific regulatory acronyms and terms (FTL, TLC, CTE, KDE, Electronic Spreadsheet) to examine how stakeholders interpreted, resisted, or reframed the specific data work structures imposed by the policy.
  3. Synthesis: Codes were refined, clustered into themes, and interpreted to reveal patterns of tension across individual, environmental, and policy levels.

Key Findings
The study identifies three primary tensions arising from the reconfiguration of stakeholders into data workers:

1. Individual Burdens (Educational, Labor, and Financial):

   • Educational: Stakeholders, particularly small-scale operators, face steep learning curves to understand new terminology (e.g., Critical Tracking Events, Key Data Elements) and digital tools. The shift from paper to digital records is described as a profound identity shift from food production experts to data collectors.
   • Labor: Significant manual labor is required to digitize existing paper records, especially when interacting with exempt upstream entities. This creates a "digitization burden" that falls disproportionately on downstream entities.
   • Financial: Costs associated with hiring staff, purchasing software, and data storage are cited as prohibitive for small businesses, particularly those just above the $25,000 annual sales exemption threshold.

2. Production Environment Infeasibility:

   • Infrastructural Limitations: The Rule assumes universal access to reliable internet and digital devices. Rural stakeholders often lack the connectivity required to submit electronic spreadsheets within the mandated 24-hour window during contamination events.
   • Cultural Infrastructures: Certain groups, such as the Amish, intentionally opt out of digital technologies for religious or personal reasons. The Rule's reliance on digital recordkeeping creates a conflict with these identities, effectively excluding them or forcing non-compliance.
   • Fluid Production Practices: The Rule's rigid categories (e.g., "shipping," "receiving," "first receiving") fail to map onto fluid, real-world practices like cross-docking or diversified farming where crop locations rotate. Stakeholders report confusion and infeasibility when trying to force complex, non-linear supply chains into discrete data fields.

3. Policy Ambiguity Masquerading as Flexibility:

   • The Rule's refusal to mandate specific technologies (to allow "flexibility") results in a lack of interoperability standards. Stakeholders are left to interpret how to structure their data, leading to duplicated efforts, misaligned investments, and uncertainty about whether their systems will communicate with others.
   • This ambiguity shifts the burden of technical coordination and standardization onto individual stakeholders, undermining the very goal of a harmonized, interoperable system.

Key Contributions

• Empirical Account of Data Labor: The paper provides a detailed empirical account of how data-driven policy reconfigures agri-food stakeholders into data producers, highlighting the invisible labor required to sustain such systems.
• Identification of Tensions: It delineates three specific points of tension (individual, environmental, and policy-level) that arise when data-driven governance is imposed at a national scale on diverse supply chains.
• Reframing Stakeholders: The authors argue that stakeholders reconfigured as data workers should be recognized as "meaningful policy partners" rather than merely actors subject to compliance obligations.
• CSCW Role in Governance: The paper suggests that the CSCW community can play a critical role in uncovering invisible burdens, supporting participatory democratic mechanisms for stakeholders to voice concerns, and aiding stakeholders in "making-do" with imposed data work.

Significance and Claims
The paper claims that well-intentioned federal policies can inadvertently reinforce existing power imbalances by disproportionately burdening those with the least resources. By applying a Data Feminist lens, the authors demonstrate that "equal" treatment in policy design often leads to inequitable outcomes in practice because it ignores the material and cultural prerequisites for compliance.

The authors modestly claim that their work contributes to the CSCW literature by adding a case study of how data-driven governance creates inequitable data work. They do not propose a specific new software solution or a legislative overhaul. Instead, they argue for a shift in perspective: recognizing the labor of data compliance, acknowledging the structural constraints of policy implementation (such as statutory prohibitions on mandating specific technologies), and exploring how CSCW can support more democratic and equitable forms of data-driven policy work. The paper emphasizes that addressing these tensions requires moving beyond viewing stakeholders as passive recipients of regulation to viewing them as essential partners whose lived realities must inform policy design.