Kansas on the hook to pay $40 million for food assistance under federal changes 30%

By Roger Nomer13%

7/23/2026, 9:00:00 AM

BS Summary: This article contains 23 faulty reasoning types, including Appeal to Emotion, Post Hoc (False Cause), and Pessimism Bias, with Negativity Bias as the most egregious example at 15.3% saturation with 154 hits. Analysis detected 1,230 faulty-reasoning hits from 1,009 analyzed words, generating a BS Score of 39.7% and a BS Rank of 30% (14,975 of 21,176 articles). This article is better (less manipulative) than 70.70% of the article peer group.

Kansas and Missouri have made progress to lower their food assistance program payment error rates, but still may have to pay millions for the program next year because of changes made in the One Big Beautiful bill. 
States will have to pay a portion of their Supplemental Nutrition Assistance Program benefits if their payment error rate is 6% or higher. 
Those states will also have to pay a higher share of administrative costs. 
Under the current plan, Kansas would have to pay around $40 million, and Missouri’s share would be $151 million. 
Pasta on the Plains: A new Kansas-grown wheat could soon be in your box of noodles 
Pasta made from durum wheat line the shelves at a grocery store. 
Anna Pope / Harvest Public Media 
Under the One Big Beautiful Bill, states will have to pay a portion of SNAP food assistance benefits if they have an error rate of 6%. 
Elizabeth Keever is the chief resource officer with Harvesters, a regional food bank. 
She said this cost shift puts SNAP benefits at risk. 
“There is a reality that if states can't pay and they simply don't have it in their budgets, the SNAP program in states will cease to exist,” Keever said. 
“And frankly, that's terrifying.” 
Keever and others are seeking delays in the changes as states adapt. 
The error rate is a measure of accuracy for SNAP food benefit payments. 
According to the U.S. 
Department of Agriculture, these payment errors are largely unintentional underpayments or overpayments. 
The error rate is not considered a metric for measuring fraud. 
Every June, the USDA analyzes data collected from the states and uses it to determine national and state payment error rates. 
The most recent national average payment error rate is 10.62%. 
Kansas had a rate of 9.4%, a slight decrease from 9.9% in 2024. 
Missouri’s error rate is 8.7%, down from 9.42% in 2024. 
Ty Jones Cox is the vice president for food assistance at the Center on Budget and Policy Priorities, a nonpartisan research and policy institute. 
She said states are already erecting access barriers to SNAP because they’re concerned about the coming large payments. 
“The only thing they can control is how to reduce their errors super quick, and that’s by making it more complicated for families to get on SNAP,” Jones Cox said. 
These barriers include asking for more verification and asking people to renew certification more often, which can also reduce the program’s numbers as people get frustrated with the process and leave. 
“It's really complicated when you have to verify everything from who's in your home, to maybe your medical expenses, to every detail of your life,” Jones Cox said. 
Keever said the error rates have been affected by other factors aside from payment errors. 
The government shutdown last year created a lot of confusion around SNAP benefits being paid out. 
“That really made opportunities for more technical errors to come out,” Keever said. 
“Any time that you divert from the normal process, you have challenges for there to be mistakes.” 
The One Big Beautiful Bill also changed eligibility for certain individuals, with little time for state agencies to work out systems to implement the changes, Keever said. 
That also led to potentially more errors in the application process. 
“There has not been enough time for agencies to be able to adequately lower their error rates,” Keever said. 
“Both Kansas and Missouri have made progress on getting theirs down, but it's not where we need to be.” 
These complications from the cost shifts come as SNAP enrollment is dropping dramatically from cuts outlined in the One Big Beautiful Bill. 
Between last July, when the law was enacted, and April, SNAP participation fell by more than 4.5 million people nationwide, an 11% drop in nine months. 
In Kansas, enrollment fell more than 21,000 in that time frame, a decrease of about 11%. 
In Missouri, there’s been almost a 50,000 drop in enrollment, a decrease of about 7%. 
“SNAP is in the middle of the steepest, fastest decline in participation in decades, and it's not because the need is any lower,” Jones Cox said. 
“We are facing a hunger crisis that Congress has the power to mitigate if they course correct.” 
Hunger relief agencies like Harvesters are urging lawmakers to delay the changes to SNAP until states can adjust. 
Letters signed by a bipartisan group of 210 mayors and the National Governors Association are both asking Congress the same thing. 
“We need Congress to delay these changes, or else we are going to see the SNAP benefits disappear across the country, state by state, because states cannot afford the additional dollars for these programs,” Keever said. 
Hunger relief agencies fear the ultimate result of the cost shift will be narrowing eligibility or states dropping SNAP altogether. 
The American Public Human Services Association recently surveyed all 50 state SNAP agencies about their plans for dealing with the cost shift. 
In the survey, 29% of the states identified narrowing eligibility policies as a risk, and 11% of the states are considering withdrawal from SNAP. 
Even if the action isn’t as drastic as withdrawing from SNAP, states will need to find some way to make up these costs. 
A delay would give states more time to figure out how to deal with the changes in a way that preserves hunger programs. 
“We've heard of states saying they're no longer going to have universal school meals potentially,” Jones Cox said. 
“Some states are opting out of summer EBT. 
This is why states need more time, to both figure out and reduce their errors without cutting people off.” 
Roger Nomer reports from the Wichita area for the Kansas News Service. 
You can email him at nomer@kmuw.org. 
The Kansas News Service is a collaboration of KMUW, KCUR, Kansas Public Radio and High Plains Public Radio. 
Kansas News Service stories and photos may be republished by news media at no cost with proper attribution and a link to ksnewsservice.org. 
Article reasoning-pattern comparisonThis article: 8.3%Roger Nomer: 1.2%Columbia Missourian: 1.7%Confirmation Bias8.3%This article: 1.9%Roger Nomer: 0.7%Columbia Missourian: 0.8%Anchoring Bias1.9%This article: 3.4%Roger Nomer: 1.0%Columbia Missourian: 2.7%Availability Heuristic3.4%This article: 1.8%Roger Nomer: 0.2%Columbia Missourian: 0.9%Representativeness Heuristic1.8%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.4%Hindsight Bias0.0%This article: 2.7%Roger Nomer: 1.3%Columbia Missourian: 1.3%Overconfidence Bias2.7%This article: 3.6%Roger Nomer: 2.6%Columbia Missourian: 5.5%Framing Effect3.6%This article: 1.4%Roger Nomer: 0.7%Columbia Missourian: 1.0%Loss Aversion1.4%This article: 3.0%Roger Nomer: 0.8%Columbia Missourian: 0.7%Status Quo Bias3.0%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.3%Sunk Cost Effect0.0%This article: 2.3%Roger Nomer: 4.7%Columbia Missourian: 4.5%Optimism Bias2.3%This article: 10.9%Roger Nomer: 1.8%Columbia Missourian: 1.6%Pessimism Bias10.9%This article: 15.3%Roger Nomer: 2.2%Columbia Missourian: 5.4%Negativity Bias15.3%This article: 0.0%Roger Nomer: 0.4%Columbia Missourian: 1.7%Self-Serving Bias0.0%This article: 1.8%Roger Nomer: 0.3%Columbia Missourian: 0.6%Fundamental Attribution Error1.8%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.2%Actor-Observer Bias0.0%This article: 0.0%Roger Nomer: 2.4%Columbia Missourian: 1.6%In-Group Bias0.0%This article: 0.0%Roger Nomer: 0.5%Columbia Missourian: 0.4%Out-Group Homogeneity Bias0.0%This article: 0.0%Roger Nomer: 1.3%Columbia Missourian: 2.4%Halo Effect0.0%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.0%Horn Effect0.0%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.0%Dunning-Kruger Effect0.0%This article: 3.9%Roger Nomer: 0.8%Columbia Missourian: 0.9%Recency Bias3.9%This article: 0.0%Roger Nomer: 0.3%Columbia Missourian: 0.3%Primacy Effect0.0%This article: 0.0%Roger Nomer: 0.1%Columbia Missourian: 0.0%Blind-Spot Bias0.0%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.5%Ad Hominem0.0%This article: 0.0%Roger Nomer: 0.3%Columbia Missourian: 0.2%Straw Man0.0%This article: 1.2%Roger Nomer: 1.4%Columbia Missourian: 2.9%Appeal to Authority1.2%This article: 9.4%Roger Nomer: 1.7%Columbia Missourian: 1.1%False Dilemma9.4%This article: 8.4%Roger Nomer: 1.3%Columbia Missourian: 1.0%Slippery Slope8.4%This article: 0.0%Roger Nomer: 0.2%Columbia Missourian: 0.1%Circular Reasoning0.0%This article: 4.1%Roger Nomer: 3.0%Columbia Missourian: 3.6%Hasty Generalization4.1%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.2%Red Herring0.0%This article: 2.1%Roger Nomer: 0.3%Columbia Missourian: 0.7%Bandwagon2.1%This article: 14.1%Roger Nomer: 8.9%Columbia Missourian: 5.3%Appeal to Emotion14.1%This article: 0.0%Roger Nomer: 0.6%Columbia Missourian: 0.6%Begging the Question0.0%This article: 11.1%Roger Nomer: 2.3%Columbia Missourian: 2.0%Post Hoc (False Cause)11.1%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.0%Tu Quoque0.0%This article: 0.0%Roger Nomer: 0.4%Columbia Missourian: 0.4%Burden of Proof0.0%This article: 0.0%Roger Nomer: 0.8%Columbia Missourian: 0.2%Appeal to Nature0.0%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.2%Composition/Division0.0%This article: 5.4%Roger Nomer: 1.4%Columbia Missourian: 2.6%Anecdotal5.4%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.1%No True Scotsman0.0%This article: 1.1%Roger Nomer: 0.8%Columbia Missourian: 1.3%Ambiguity (Equivocation)1.1%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Roger Nomer: 0.1%Columbia Missourian: 0.1%Middle Ground0.0%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.0%Personal Incredulity0.0%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.1%Special Pleading0.0%This article: 0.0%Roger Nomer: 0.1%Columbia Missourian: 0.1%Genetic Fallacy0.0%This article: 0.0%Roger Nomer: 0.5%Columbia Missourian: 0.8%Unattributed Quote0.0%This article: 0.0%Roger Nomer: 0.3%Columbia Missourian: 0.7%Quote-first Misdirection0.0%This article: 5.1%Roger Nomer: 0.7%Columbia Missourian: 2.9%Biased Writer Voice5.1%This article: 0.0%Roger Nomer: 1.5%Columbia Missourian: 1.3%Indoctrination0.0%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.7%Politically Left Leaning Bias0.0%This article: 0.0%Roger Nomer: 0.0%Columbia Missourian: 0.2%Politically Right Leaning Bias0.0%This article: 0.0%Roger Nomer: 0.5%Columbia Missourian: 1.6%Attempt to Sell a Product or S…0.0%

1009 words analyzed.

Speakers

4speakers37%attributed speech640writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 14 words • 100.0% coverageWriter's voice • 37 words • 100.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageElizabeth Keever • 10 words • 0.0% coverageElizabeth Keever • 29 words • 0.0% coverageElizabeth Keever • 4 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageTy Jones Cox • 18 words • 0.0% coverageTy Jones Cox • 30 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageTy Jones Cox • 28 words • 0.0% coverageKeever • 15 words • 0.0% coverageKeever • 16 words • 0.0% coverageKeever • 13 words • 0.0% coverageKeever • 17 words • 0.0% coverageKeever • 27 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageKeever • 19 words • 0.0% coverageKeever • 19 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageJones Cox • 26 words • 0.0% coverageJones Cox • 17 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageKeever • 36 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageJones Cox • 18 words • 0.0% coverageJones Cox • 8 words • 0.0% coverageJones Cox • 19 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverage
Selected voice

Elizabeth Keever

100%flagged-word coverage
43 attributed words12% of attributed speech41% writer coverage
0%5.0%10.0%Biased Writer Voice-8.0 ptsWriter: 8.0%Elizabeth Keever: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.