Racial equity in local food incentive programs: Examining gaps in data and evaluation

Since 2002, over 60 local food procurement incentive bills for schools and early care sites have been introduced in state legislatures


Introduction
Between 2002 and 2020, 61 state-level local food procurement incentive bills for schools or early care sites were introduced, and 23 passed.Of the 61 bills proposed, just 13 contained any form of program reporting or evaluation.Of those 13, nine were passed (National Farm to School Network & Vermont Law School, 2021).Evaluation is essential to assessing the impact and effectiveness of farm-to-school policy and informing future efforts.Evaluation specifically should include data collection and analysis on the racial equity impacts of farm-to-school policies and programs to identify potential gaps in demographic reach, degree of cultural relevance, and impact on children of color and producers of color.This level of policy analysis is vital to developing future farm-to-school policies and approaches that correct instead of perpetuate racist and oppressive systems.A lack of legislatively mandated data collection makes it difficult to assess the quantitative impacts and outcomes of policies.This commentary discusses the challenges associated with the lack of data and evaluation of local food procurement incentive policies and elevates recommendations to better inform future farm-to-school policy and policy evaluation.

Data Barriers to Farm-to-School and Early Care and Education Evaluation
A major barrier in capturing sufficient information to understand the impacts of incentive policy is that the policy frequently omits evaluation.Although data may be collected by organizations receiving funding for local procurement, the data are not being tracked or reported in a systematic manner.Additionally, if data collection was not planned before policy implementation, important indicators for evaluation may be missed, especially indicators around equity.Even if an outside organization procures funding for evaluation, the available data are often of poor quality, making it difficult to conduct meaningful analyses, particularly around the racial equity impact of the policy.The D.C. Healthy Tots Act is an example of a policy that did not include evaluation (Stephens et al., 2021).The reporting and tracking systems for the D.C. Healthy Tots Act's Local51 specific reimbursement numbers, race and ethnicity data, and free and reduced-price meal eligibility rates were incomplete, limiting the analyses of the reach and impact of the program.The Oregon Farm to School Grant Program policy also did not include evaluation.This limited the quality of baseline data because districts were not required to track information on local food purchases before receiving grant funding (Giombi et al., 2018).In the Oregon evaluation, analyses of the impact on farmers and local produce purchases were limited and included no information on producer demographics.Researchers and policymakers would gain a better understanding of the impacts of these policies if organizations required systematic reporting that produces higher quality data from the schools and childcare sites as well as the producers.
While policymakers often tout the economic impacts of farm-to-school programs when trying to pass policy, limited data exist on how these policies affect producers, particularly Black, Indigenous, and other people of color (BIPOC) producers.In our evaluation of the D.C. Healthy Tots Act that examined how farm to early care and education (ECE) policy affects local food intermediaries and local producers, we found that had it not been for a local food aggregator, FRESHFARM, we would have had no producer data because ECE sites and the state agency were not capturing and aggregating the data.In Oregon, data were collected from the school districts, but no data were collected from or about producers.An essential step in furthering equity in farm-to-school policy is tracking sales and disaggregating data by producer race to understand better who is benefitting or being excluded from the policy.Furthermore, it is important to consider more nuanced evaluation measures and approaches to understand if and how policies are building business opportunities and supporting access to school markets for producers.

Recommendations
From our work on evaluating farm-to-school and ECE policies, we have three recommendations for making evaluations more robust to better inform future policy.First, establish partnerships with universities and nonprofit partners to support evaluation planning, implementation, and/or data collection, perhaps even during the phase of legislative development.These partners can alleviate the burden on the school districts and bring a level of expertise in data collection and evaluation that can help inform the policy language and implementation.Partners with expertise in evaluation centered in racial equity can also support and inform the prioritization of equity measures and approaches.Furthermore, external partners may have the capacity to capture more than just procurement data.For example, Michigan State University's Center for Regional Food Systems surveyed school foodservice directors on their motivators, barriers, and challenges to purchasing and serving local foods and participating in the incentive program (Matts et al., 2020).
Having these partners at the table can also set the stage for including the costs of evaluation in policy budgets.For example, Colorado State University was involved in developing the farm-to-school policy in Colorado (School Incentives to Use Colorado Food and Producers, 2019).Though the evaluation portion of the bill was not funded, it provides a model for including evaluation in policy language.In another example, Michigan State University's Center for Regional Food Systems has been involved in data collection for the state's "10 Cents a Meal for Michigan's Kids and Farms" program.In this example, systems were better established to collect data and leverage supplemental resources for analyzing the data collected through state agency partners.Additionally, when it comes to being able to disaggregate data, third parties may have more capacity to layer existing demographic data over incentive participation data.
Our second recommendation is to identify populations of potential impacts and outcome measures prior to implementation to collect the most valuable data for evaluation.Populations of interest may be schoolchildren, school foodservice operations, school decision-makers, parents, and/or producers.Once populations of interest are identified, implementers and evaluators need to engage these groups in informing and developing measures and metrics.What aspects of the program are most important to the community involved?What outcomes do they want to see?What outcomes are needed to continue the policy in the future?These are all important questions that should be considered when developing an evaluation plan.
Outcomes and impacts for producers, specifically BIPOC producers, have been difficult to examine with existing data.By elevating BIPOC producers as key stakeholders of interest and establishing outcomes that are a priority for this population, we can further the exploration and conversation around equity of farm-to-school policy.Furthermore, it is important to ensure that outcome measures are reflective of the population identified and take into account the nuances of the community and culture (e.g., willingness to try culturally relevant foods; equipment or training needs identified by school foodservice staff; and profit or amount of product delivered for producers).
Our third recommendation is to develop easy-to-use reporting templates and systems that are a mandatory part of participation for schools and/or ECE programs receiving funding for local food procurement.These templates should strive to include data on producers.For example, the Michigan Department of Education worked with FarmLogix, a Chicago-based firm that supplies technology solutions, to support an electronic platform for school foodservice directors to track their purchases of local foods used for the program (Matts et al., 2020).Furthermore, in surveys conducted by the Oregon Department of Education and Michigan State University's Center for Regional Food Systems, foodservice providers were asked to provide names of producers they had worked with and to share feedback received from food producers, processors, and distributors with whom they had worked to purchase product.This information is a start to understanding equitable access to these programs for producers, but more rigorous data collection is needed.
As part of this recommendation, an option would be to shift most of the burden from school districts and instead have a third party or state agency track data directly from producers.FRESHFARM in Washington, D.C., is a prime example (Stephens, 2021).Another example is New Mexico's Approved Supplier Program (New Mexico Farmers Market Association, 2021).During the 2018-2019 school year, New Mexico's Public Education Department (NMPED) piloted a cooperative that worked with school districts to streamline procurement and vendor requirements needed to sell to schools by establishing a list of approved vendors.The cooperative also supported small producers of color.Distributors are also well positioned to capture producer information and share aggregated purchasing information back to districts or evaluators.Either way, ideally, the policy would include funding to create or expand data collection systems.

Conclusion
Better data collection and use of data can help inform and drive more equitable farm-to-school and farm-to-ECE policy.Equity-centered approaches to evaluation should be explored to capture the experiences and impacts on multiple stakeholders.The ideal would be to build equity into the policy language and priorities, thus paving the way for equity-focused evaluation, such as including support for small farmers and BIPOC producers, and prioritizing reach to communities that have been historically disinvested.Significant work still needs to be done to create foundations to support equitable evaluation.This includes advancing community-driven evaluation that defers to impacted stakeholders and developing consistent and clear policy language that prioritizes BIPOC producers without creating an undue burden on them to obtain "minority certifications."Furthermore, data collection and reporting must always be balanced with the burden on practitioners.Partnerships with academic and community partners, leadership and data collection from state agencies, and transparency in the supply chain can reduce the burden on both nutrition staff and producers.