Crescent City Farmers Market programs give free food to mothers 

My home market organization continues to pilot new ways to include at-risk populations into their community. The staff shared with me that they studied the Sustainable Food Center’s work in Austin TX with CVB to design their pilot. This mock program will lead the state into seeing how WIC families benefit from markets in terms of social and intellectual capital as well as increasing their regular access to healthy food.

(The article seems to state that CCFM has been doing SNAP redemptions since 2008; actually it has been accepting EBT cards to redeem SNAP benefits since 2005 and doing market matches on different programs since before then, including a seafood bucks program and a FMNP reward program for seniors to spend once they spent their FMNP coupons. The incentive added to SNAP has been a program in existence at the market since around 2008.)

Market Umbrella deserves credit for its continued innovation and the staff and board’s willingness to constantly explore ways to increase their markets’ reach.

Crescent City Farmers Market programs give free food to mothers | NOLA.com

SNAP Update:  “Twinkies can no longer be considered bread”

      “I’m disappointed that the rules don’t go as far as what was proposed early this year,” said Danielle Nierenberg, president of Food Tank, a nutrition advocacy group. “USDA has missed an opportunity to increase the availability of and access to healthier foods for low-income Americans.”

The earlier proposals also recommended leaving food with multiple ingredients like frozen pizza or canned soup off the staple list. The outcome is a win for the makers of such products, like General Mills Inc. and Campbell Soup Co., which feared they would lose shelf space as retailers added new items to meet the requirements.

But retailers still criticized the new guidelines as too restrictive. Stores must now stock seven varieties of staples in each food category: meat, bread, dairy, and fruits and vegetables….

…More changes to the food-stamp program may lie ahead. The new rules were published a day after the House Committee on Agriculture released a report* calling for major changes to the program, which Republicans on the committee say discourages recipients from finding better-paid work.

Source: Regulators Tweak SNAP Rules for Grocers – WSJ

*Some of the findings from the 2016 Committee on Agriculture Report “Past, Present, and Future of SNAP” are below.

    • Program participation nearly doubled (up 81 percent from FY 2007 to FY 2013) as a result of the recent recession. In an average month in FY 2007, 26.3 million people (or about 9 percent of the U.S. population) were enrolled in SNAP. That increased to 47.6 million people (or about 15 percent of the U.S. population) in FY 2013, owing to the fact that the economy was slow to recover and many families remained reliant on SNAP. Even now, with a 4.6 percent unemployment rate (compared to a 9.6 percent unemployment rate for 2010), there were still 43.4 million SNAP participants as of July 2016.
    • SNAP is now a catchall for individuals and families who receive no or lower benefits from other welfare programs, largely because the eligibility criteria in SNAP are relatively more relaxed. As a result, the net effect has been to increase SNAP enrollment. For example, in the welfare reforms of 1996, the cash welfare program Aid to Families with Dependent Children (AFDC) was converted into a block grant known as TANF, which has rather rigorous work and activity requirements and includes a time limit. Another program available to those who are laid off from work is Unemployment Insurance (UI). These benefits require individuals to have a work history and to be fired through no fault of their own to be eligible for assistance. UI benefits are also time-limited, typically lasting six months. A third program, Federal disability benefits, requires individuals to prove they are unable to work. For many families who have not collected SNAP in the past, SNAP is now a default option for filling in the gaps.
    • USDA data shows that spending on SNAP remains three times what it was prior to the recession ($23.09 billion pre-recession average compared to $73.99 billion post-recession in FY 2015). However, SNAP spending is now projected to be significantly lower than it was estimated at passage of the 2014 Farm Bill.
    • For FY 2017, the maximum monthly benefit in the 48 contiguous states and DC is $194 for a one-person household, $357 for a two-person household, and $649 for a four-person household.17 In determining a household’s benefit, the net monthly income of the household is multiplied by 30 percent (because SNAP households are expected to spend 30 percent of their income on food), and the result is subtracted from the maximum benefit to determine the household’s benefit.
    • Seniors have the lowest rates of SNAP participation among eligible households of any demographic. While the low participation rate has a variety of causes, a prominent explanation is the stigma associated with SNAP and welfare in general. Many factors contribute to a lack of access to food among seniors, including a lack of a substantial income, the gap between Medicaid and the cost of living, limited income with specialized diets, and mental and physical illnesses.  The issues facing these populations must be viewed holistically, with SNAP as one piece of a larger solution to solving hunger for seniors.


According to research by the AARP Foundation—a charitable affiliate of AARP—over 17 percent of adults over the age of 40 are food-insecure. Among age cohorts over age 50, food insecurity was worse for the 50-59 age group, with over 10 percent experiencing either low or very low food security. Among the 60-69 age cohort, over 9 percent experienced similar levels of food insecurity, and over 6 percent among the 70+ population.

• The operation of the program is at the discretion of each state. For instance, in California, SNAP is a county-run program. In Texas, SNAP is administered by the state… Dr. Angela Rachidi of the American Enterprise Institute cited a specific example in New York City where SNAP, WIC, school food programs, and child and adult care programs are all administered by different agencies and the result is that each agency must determine eligibility and administer benefits separately.

K. Michael Conaway, Chairman of the House Committee on Agriculture. Hearing of the House of Representatives, Committee on Agriculture. Past, Present, and Future of SNAP. February 25, 2015. Washington, D.C.  Find report here

From CNN this week:

The number of people seeking emergency food assistance increased by an average of 2% in 2016, the United States Conference of Mayors said in its annual report Wednesday.

The majority, or 63%, of those seeking assistance were families, down from 67% a year ago, the survey found. However, the proportion of people who were employed and in need of food assistance rose sharply — increasing to 51% from 42%.

 

CNN Money report

 

Know Your Farmer, Know Your USDA

Excellent interview with USDA/AMS Administrator, Elanor Starmer.

 

She shares the success to date and paints a picture of invigoration that includes Know Your Farmer Know your Food, Farm To School, Urban Agriculture and a wide spectrum of programs and citizen initiatives that is reaching millions.

 

 

 

 

Interested in Free SNAP EBT Equipment?

If you are a farmers market or a direct marketing farmer interested in offering card processing but currently lack EBT equipment, check out Farmers Market Coalition’s link below to get information about two programs that offer free equipment and cover many of the fees for a period. The site is easy to navigate to see if your market or business can begin EBT processing. FMC also supplies some good FAQs here for anyone searching for more information on these systems.

Source: Interested in Free SNAP EBT Equipment?

The Truth About Poor People’s Eating Habits Will Surprise You 

A recent Centers for Disease Control survey of 5,000 American children and adolescents age 2 to 19 offers proof that poor people not only don’t consume more fast food than those with higher incomes, they actually consume slightly less. The study, which looked at figures from 2011-’12, found that “no significant difference was seen by poverty status in the average daily percentage of calories consumed from fast food among children and adolescents aged 2 to 19.” In fact, the poorest children surveyed got the least amount of their daily calorie intake from fast food, at just 11.5 percent. That number rose to 13 percent for their more affluent peers.

And a Gallup poll from 2013 found “[t]hose earning the least actually are the least likely to eat fast food weekly — 39% of Americans earning less than $20,000 a year do so.” Conversely, more affluent Americans — “those earning $75,000 a year or more — are more likely to eat [fast food] at least weekly (51%) than are lower-income groups.”

Source: The Truth About Poor People’s Eating Habits Will Surprise You | Alternet

Big Data and Little Farmers Markets, Part 3

I used these examples in Part 2 of this series, but wanted to use them again for this post. To review:

Market A (which runs on Saturday morning downtown) is asked by its city to participate in a traffic planning project that will offer recommendations for car-free weekend days in the city center. The city will also review the requirement for parking lots in every new downtown development and possibly recalibrate where parking meters are located. To do this, the city will add driving strips to the areas around the market to count the cars and will monitor the meters and parking lot uses over the weekend. The market is being asked for its farmers to track their driving for all trips to the city and ask shoppers to do Dot Surveys on their driving experiences to the market on the weekend. Public transportation use will be gathered by university students.

Market B is partnering with an agricultural organization and other environmental organizations to measure the level of knowledge and awareness about farming in the greater metropolitan area. For one summer month, the market and other organizations will ask their supporters and farmers to use the hashtag #Junefarminfo on social media to share any news about markets, farm visits, gardening data or any other seasonal agricultural news.

Market C is working with its Main Street stores to understand shopping patterns by gathering data on average sales for credit and debit users. The Chamber of Commerce will also set up observation stations at key intersections to monitor Main Street shopper behavior such as where they congregate.

Market D has a grant with a health care corporation to offer incentives and will ask those voucher users to track their personal health care stats and their purchase and consumption of fresh foods. The users will get digital tools such as cameras to record their meals, voice recorders to record their children’s opinions about the menus (to upload on an online log) with their health stats such as BP, exercise regimen. That data will be compared to the larger Census population.

So all those ideas show how markets and their partners might be able to begin to use the world of Big Data. In those examples, one can see how the market benefits from having data that is (mostly) collected without a lot of work on the market’s part and yet is useful for them and for the larger community that the market also serves.

However, one of the best ways that markets can benefit from Big Data is slightly closer to home and even more useful to the stability and growth of the market itself. That is: to analyze and map the networks that markets foster and maintain, which is also known as network theory.
Network theory is a relatively new science that rose to prominence in the 1980s and 1990s and is about exploring and defining the relationships that a person or a community has and how, through their influence, their behavior is altered. What’s especially exciting about this work is that it combines many disciplines from mathematics to economics to social sciences.

A social network perspective can mean that data about relationships between the individuals can be as useful as the data about individuals themselves. Some people talk about this work in terms of strong ties and weak ties. Strong ties are the close relationships that we use with greater frequency and offer support and weak ties are those acquaintances who offer new information and connect us to other networks. The key is that in order to really understand a network, it is important to analyze the behavior of any member of the network in relation to other members action. This has a lot to do with incentives, which is obviously something markets have a lot of interest in.

From the book Networks, Crowds, and Markets: Reasoning about a Highly Connected World. By David Easley and Jon Kleinberg. Cambridge University Press, 2010. Complete preprint on-line at http://www.cs.cornell.edu/home/kleinber/networks-book/

From the book Networks, Crowds, and Markets: Reasoning about a Highly Connected World.
By David Easley and Jon Kleinberg. Cambridge University Press, 2010.
Complete preprint on-line at http://www.cs.cornell.edu/home/kleinber/networks-book/

From the foodsystemsnetwork.org website

From the foodsystemsnetwork.org website

network analysis

network analysis

I could go on and on about different theories and updates and critiques on these ideas, but the point to make here is this is science that is so very useful to the type of networks that food systems are propagating. Almost all of the work that farmers markets do rely on network theory without directly ascribing to it.

Think about a typical market day: a market could map each vendors booth to understand what people come to each table, using Dot Surveys or intercept surveys. That data could assist the vendor and the market. The market will benefit in knowing which are the anchor vendors of the market, which vendors constantly attract new shoppers, which vendors share shoppers etc. The market could also find out who among their shoppers bring information and ideas into the market and who carrries them out to the larger world from the market. All of this data would be mapped visually and would allow the market to be strategic with its efforts, connecting the appropriate type of shoppers to the vendors, expanding the product list for the shoppers likely to purchase new goods and so on.

Network theory would be quite beneficial to markets in their work to expand the reach to benefit program users and in the use of incentives. Since these market pilots began around 2005/2006, it has been a struggle to understand how to create a regular, return user of markets among those who have many barriers to adding this style of health and civic engagement. Those early markets created campaigns designed to offer the multiple and unique benefits of markets as a reason for benefit program shoppers to spend their few dollars there. Those markets also worked to reduce the barriers whenever possible by working with agencies on providing shuttles, offering activities for children while shopping, and adding non-traditional hours and locations for markets. Those efforts in New York, Arizona, California, Maryland, Massachusetts and Louisiana (among others) were positive but the early results were very small, attracting only a few of the shoppers desired. When the outcomes were analyzed by those organizations, it seemed that a few issues were cropping up again and again:
1. The agency that distributed the news of these market programs didn’t understand markets or did not have a relationship of trust with their clients that encouraged introduction of new ideas or acceptance of advice in changing their habits.
2. The market itself was not ready to welcome new benefit program shoppers- too few items were available or the market was not always welcoming to new shoppers who required extra steps and new payment systems.
3. Targeting the right group of “early adopters” among the large benefit program shopping base was impossible to decipher.
4. Some barriers remained and were too large for markets alone to address (lack of transportation or distance for example).
4. Finding the time for staff to do all of that work.

Over time, markets did their best to address these concerns, which has led to the expansion of these systems into every state and a combined impact in the millions for SNAP purchases at markets alone. The cash incentives assisted a great deal, especially with #2 and #4. However, this work would be made so much easier and the impact so much larger if network theory was applied.
Consider:
Market A is going to add a centralized card processing system and has funds to offer a cash incentive. But how to spend it? And how to prepare the market for the program?

If the market joined forces with a public health agency and a social science research team from a nearby university, it might begin by mapping the networks in that market to understand the strong and weak ties it contains as well as the structural holes in its network. It might find out that its vendors attract few new shoppers regularly or that the market’s staff is not connected to many outside actors in the larger network, thereby reducing the chance for information to flow.
It might also see that younger shoppers are not coming to the market and therefore conclude that focusing its efforts on attracting older benefit program shoppers (especially at first) might be a strategic move. If the market has a great many low-income shoppers using FMNP coupons already, the mapping of those shoppers may offer much data about how the market supports benefit program shoppers already and how it might expand with an audience already at market
The public health agency might do the same mapping for the agencies that are meant to offer the news of the market’s program. That mapping might find certain agencies or centers are better at introducing new ideas or have a population that is aligned already with the market’s demographic and therefore likely to feel welcomed.

As for incentives, what markets and their partners routinely tell me is more money is not always the answer. Not knowing what is expected from the use of the incentives or how to reach the best audience for that incentive is exhausting them or at least, puzzling them.
If markets knew their networks and knew where the holes were, they could use their incentive dollars much more efficiently and run their markets without burning out their staff or partners.
They might offer different incentives for their different locations, based on the barriers or offerings for each location. (They may also offer incentives to their vendors to test out new crops.)
If connectors are seen in large numbers in a market, then a “bring a friend” incentive might be offered, or if the mapping shows a large number of families entering the system in that area, then an incentive for a family level shopping experience may be useful.
One of the most important hypotheses that markets should use in their incentive strategy is how can they create a regular shopper through the use of the incentive. Of course, it is not the only hypothesis for a market; a large flagship market might identify their role as introducing new shoppers to their markets every month and use their funds to do just that. But for many markets with limited staff and small populations in and around the market, a never-ending cycle of new shoppers coming in for a few months and then not returning may not be the most efficient way to spend those dollars or their time. So this is also where network theory could be helpful.
By asking those using their EBT card to tell in detail where and how they heard about the program and by also tracking the number of visits they have after their introduction, we could begin to see which introductions work the best. Or by asking a small group of new EBT shoppers to be members of a long-term shopping focus group to track what happens during their visit (how many vendors they purchase from and how long they stay) and after (see Market D example at the top), we could learn about what EBT shoppers in that area value in their market experience. We may also find out that the market has few long-term return shoppers from the EBT population or we may find out that connectors become easy to spot and therefore they can be rewarded when sharing information on the market’s behalf.
In all of these cases, it will be easier for the staff to know what to do and when to do it if they understand their networks both in and around the market.
And of course, mapping the larger food systems around the markets’ systems would be exciting and could move policy issues to action sooner and allow funding to be increased for initiatives to fill the holes found.

However markets do it, what seems necessary is to know specifically who is using markets and how and why they decided to begin to use them and to whom those folks are connected. Network theory can be the best and widest use of the world of Big Data, especially to accomplish what Farmers Market Coalition has set as their call to action: that markets are for everyone.

Some reading, if you are interested:

http://www.foodsystemnetworks.org

The Tipping Point

http://www.cs.cornell.edu/home/kleinber/networks-book/networks-book-ch03.pdf

http://www.sciencemag.org/content/301/5634/827.full.pdf

http://melander335.wdfiles.com/local–files/reading-history/kadushin.pdf

FINI programs funded for FY 2015/2016

Congratulations!

USDA is funding projects in 26 states for up to 4 years, using funds from FY2014 and FY2015. USDA will issue a separate request for applications in FY16, and in subsequent years. Fiscal year 2014 and 2015 awards are:

Pilot projects (up to $100,000, not to exceed 1 year):

Yolo County Department of Employment and Social Services, Woodland, Calif., $100,000
Heritage Ranch, Inc., Honaunau, Hawaii, $100,000
Backyard Harvest, Inc., Moscow, Idaho, $10,695
City of Aurora, Aurora, Ill., $30,000
Forsyth Farmers’ Market, Inc., Savannah, Ga., $50,000
Blue Grass Community Foundation, Lexington, Ky., $47,250
Lower Phalen Creek Project, Saint Paul, Minn., $45,230
Vermont Farm-to-School, Inc., Newport, V.T., $93,750
New Mexico Farmers Marketing Association, Santa Fe, N.M., $99,999
Santa Fe Community Foundation, Santa Fe, N.M., $100,000
Guilford County Department of Health and Human Services, Greensboro, N.C., $99,987
Chester County Food Bank, Exton, Pa., $76,543
Nurture Nature Center, Easton, Pa., $56,918
Rodale Institute, Kutztown, Pa., $46,442
Rhode Island Public Health Institute, Providence, R.I., $100,000
San Antonio Food Bank, San Antonio, Texas, $100,000
Multi-year community-based projects (up to $500,000, not to exceed 4 years):

Mandela Marketplace, Inc., Oakland, Calif., $422,500
Market Umbrella, New Orleans, La., $378,326
Maine Farmland Trust, Belfast, Maine, $249,816
Farmers Market Fund, Portland, Ore., $499,172
The Food Trust, Philadelphia, Pa., $500,000
Utahns Against Hunger, Salt Lake City, Utah, $247,038
Opportunity Council, Bellingham, Wash., $301,658
Multi-year large-scale projects ($500,000 or greater, not to exceed 4 years):

Ecology Center, Berkeley, Calif., $3,704,287
Wholesome Wave Foundation Charitable Ventures, Inc., Bridgeport, Conn., $3,775,700
AARP Foundation, Washington, D.C., $3,306,224
Florida Certified Organic Growers and Consumers, Gainesville, Fla., $1,937,179
Massachusetts Department of Transitional Assistance, Boston, Mass., $3,401,384
Fair Food Network, Ann Arbor, Mich., $5,171,779
International Rescue Committee, Inc., New York, N.Y., $564,231
Washington State Department of Health, Tumwater, Wash., $5,859,307
Descriptions of the funded projects are available on the NIFA website.