KUER0%

Think you can solve some Utah problems? The Policy Project has a contest for you 49%

By Sean Higgins0%

6/12/2026, 10:21:59 AM

BS Summary: This article contains 31 faulty reasoning types, including Halo Effect, False Dilemma, and Negativity Bias, with Indoctrination as the most egregious example at 22.5% saturation with 149 hits. Analysis detected 1,672 faulty-reasoning hits from 663 analyzed words, generating a BS Score of 49.8% and a BS Rank of 49% (11,159 of 21,887 articles). This article is better (less manipulative) than 51.00% of the article peer group.

Getting period products in schools, strengthening child sexual abuse prevention and expanding the child tax credit. 
Those are just some of The Policy Project’s accomplishments over the past few years. 
Now they want to share what they’ve learned about passing policy in Utah. 
“It's so easy to get in the frame of, like, ‘This is what's wrong and I can't stand this, and the Legislature did this on purpose and they hate us,’ or something like that,” said founder and president Emily Bell McCormick. 
“And I think we always try to go with, ‘Hey, hey, you might not have noticed, but this is a problem, let us help you solve it.’” 
The group’s results speak for themselves, with an impressive track record of legislation and budget appropriation requests that were pushed across the finish line, due in no small part to McCormick and The Policy Project’s efforts. 
So, The Policy Project held an inaugural Policy Pitch Competition on June 12, where it heard detailed proposals from 115 Utahns on everything from housing to pay transparency, with three finalists presenting to a panel of state lawmakers and policy experts. 
McCormick said the real value of the competition is stress testing these ideas in front of people who could actually make some of these proposals happen. 
“I think we all are tempted to stay in echo chambers because they're nice and cozy and warm,” she said. 
”The reality is, unless you're testing this idea with a lot of people and getting broad support, it's hard to make it work.” 
One key to success is keeping things local. 
“Our best ideas have come from people who are living in Utah,” McCormick said. 
“They're everyday Utahns, they're going to work, they're coming home, they're raising a kid, they're grandparents, whatever, and they often can see there's this weird flaw in the system that's making my life a little bit more difficult, and we can kind of craft a solution around that.” 
This local, solutions-based approach resonates with lawmakers, too. 
Republican Rep. 
Tracy Miller agrees that the best legislation she sees each session comes directly from Utahns themselves, not from special interests or lobbyists. 
“A lot of our policy is coming from other states,” she said. 
“Legislators will go to conferences and go, ‘Oh, look what they did there, let's do that here.’ 
And while there may be some merit to that policy, the best policy is when it's, I think, Utah-focused.” 
For Democratic Rep. 
Verona Mauga, it’s also not enough to just have numbers and statistics on your side. 
Telling an effective story is just as important. 
“We can get all the studies and all the data and all the reports right, and we can do the math and make sense of things in that way, but the human aspect is so important,” she said. 
“I think one thing we forget to do is we get so mathematical in things that we stop humanizing each other.” 
Mauga said the competition’s format is invaluable because it’s important to listen to communities. 
“Many of these ideas are so good and well thought out,” she said. 
“I wouldn't be surprised if we see a lot of these conversations that we're having in a space like this move to the actual Legislature.” 
This year’s Policy Pitch Competition winner was Utah State University graduate student Melanie Webster for her proposal to reform the state’s criminal debt collection system. 
She took home a $10,000 prize. 
The win does not mean The Policy Project will champion her proposal next legislative session, but it could inform their future work. 
And McCormick said the competition is about more than just generating policy ideas  it’s about encouraging people to become active participants in solving community problems. 
“How do we get people to shift from thinking about, ‘Gosh, this is what's wrong in society?’ 
to, ‘Gosh, I can do something about this.’” 
Article reasoning-pattern comparisonThis article: 6.3%Sean Higgins: 2.5%KUER: 2.8%Confirmation Bias6.3%This article: 0.0%Sean Higgins: 0.9%KUER: 1.3%Anchoring Bias0.0%This article: 3.0%Sean Higgins: 2.8%KUER: 3.4%Availability Heuristic3.0%This article: 8.3%Sean Higgins: 1.7%KUER: 1.2%Representativeness Heuristic8.3%This article: 0.0%Sean Higgins: 0.4%KUER: 0.5%Hindsight Bias0.0%This article: 5.1%Sean Higgins: 2.1%KUER: 1.9%Overconfidence Bias5.1%This article: 11.3%Sean Higgins: 5.2%KUER: 7.4%Framing Effect11.3%This article: 0.0%Sean Higgins: 0.9%KUER: 1.3%Loss Aversion0.0%This article: 1.2%Sean Higgins: 1.1%KUER: 1.2%Status Quo Bias1.2%This article: 0.0%Sean Higgins: 0.1%KUER: 0.3%Sunk Cost Effect0.0%This article: 8.1%Sean Higgins: 4.1%KUER: 4.4%Optimism Bias8.1%This article: 3.3%Sean Higgins: 1.9%KUER: 2.4%Pessimism Bias3.3%This article: 17.5%Sean Higgins: 5.3%KUER: 6.3%Negativity Bias17.5%This article: 8.7%Sean Higgins: 4.2%KUER: 2.2%Self-Serving Bias8.7%This article: 3.2%Sean Higgins: 0.7%KUER: 0.9%Fundamental Attribution Error3.2%This article: 0.0%Sean Higgins: 0.2%KUER: 0.2%Actor-Observer Bias0.0%This article: 15.7%Sean Higgins: 2.7%KUER: 1.9%In-Group Bias15.7%This article: 0.0%Sean Higgins: 0.8%KUER: 0.6%Out-Group Homogeneity Bias0.0%This article: 20.4%Sean Higgins: 2.1%KUER: 2.3%Halo Effect20.4%This article: 0.0%Sean Higgins: 0.0%KUER: 0.1%Horn Effect0.0%This article: 0.0%Sean Higgins: 0.0%KUER: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Sean Higgins: 1.2%KUER: 1.2%Recency Bias0.0%This article: 0.0%Sean Higgins: 0.5%KUER: 0.3%Primacy Effect0.0%This article: 0.0%Sean Higgins: 0.1%KUER: 0.1%Blind-Spot Bias0.0%This article: 0.0%Sean Higgins: 0.5%KUER: 0.6%Ad Hominem0.0%This article: 6.2%Sean Higgins: 0.6%KUER: 0.4%Straw Man6.2%This article: 8.9%Sean Higgins: 4.1%KUER: 4.7%Appeal to Authority8.9%This article: 17.6%Sean Higgins: 2.2%KUER: 1.7%False Dilemma17.6%This article: 3.2%Sean Higgins: 0.7%KUER: 1.1%Slippery Slope3.2%This article: 2.1%Sean Higgins: 0.2%KUER: 0.2%Circular Reasoning2.1%This article: 2.6%Sean Higgins: 4.7%KUER: 4.1%Hasty Generalization2.6%This article: 0.0%Sean Higgins: 0.2%KUER: 0.2%Red Herring0.0%This article: 3.0%Sean Higgins: 0.6%KUER: 0.7%Bandwagon3.0%This article: 10.6%Sean Higgins: 5.5%KUER: 5.6%Appeal to Emotion10.6%This article: 0.0%Sean Higgins: 0.8%KUER: 0.7%Begging the Question0.0%This article: 5.4%Sean Higgins: 2.5%KUER: 2.4%Post Hoc (False Cause)5.4%This article: 0.0%Sean Higgins: 0.1%KUER: 0.1%Tu Quoque0.0%This article: 0.0%Sean Higgins: 0.3%KUER: 0.4%Burden of Proof0.0%This article: 7.2%Sean Higgins: 0.3%KUER: 0.2%Appeal to Nature7.2%This article: 0.0%Sean Higgins: 0.3%KUER: 0.3%Composition/Division0.0%This article: 9.2%Sean Higgins: 2.4%KUER: 3.1%Anecdotal9.2%This article: 2.1%Sean Higgins: 0.2%KUER: 0.1%No True Scotsman2.1%This article: 8.9%Sean Higgins: 1.8%KUER: 1.5%Ambiguity (Equivocation)8.9%This article: 0.0%Sean Higgins: 0.0%KUER: 0.0%Gambler’s Fallacy0.0%This article: 2.4%Sean Higgins: 0.2%KUER: 0.2%Middle Ground2.4%This article: 0.0%Sean Higgins: 0.1%KUER: 0.1%Personal Incredulity0.0%This article: 0.0%Sean Higgins: 0.1%KUER: 0.1%Special Pleading0.0%This article: 0.0%Sean Higgins: 0.1%KUER: 0.2%Genetic Fallacy0.0%This article: 0.0%Sean Higgins: 0.9%KUER: 0.8%Unattributed Quote0.0%This article: 4.1%Sean Higgins: 0.8%KUER: 0.7%Quote-first Misdirection4.1%This article: 7.8%Sean Higgins: 1.4%KUER: 2.2%Biased Writer Voice7.8%This article: 22.5%Sean Higgins: 2.4%KUER: 1.6%Indoctrination22.5%This article: 0.0%Sean Higgins: 1.3%KUER: 0.8%Politically Left Leaning Bias0.0%This article: 0.0%Sean Higgins: 0.3%KUER: 0.3%Politically Right Leaning Bias0.0%This article: 16.1%Sean Higgins: 0.6%KUER: 1.0%Attempt to Sell a Product or S…16.1%

663 words analyzed.

Speakers

3speakers65%attributed speech232writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 7 words • 100.0% coverageWriter's voice • 8 words • 100.0% coverageWriter's voice • 16 words • 100.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 13 words • 100.0% coverageEmily Bell McCormick • 41 words • 0.0% coverageEmily Bell McCormick • 27 words • 100.0% coverageWriter's voice • 36 words • 100.0% coverageWriter's voice • 41 words • 100.0% coverageEmily Bell McCormick • 26 words • 0.0% coverageEmily Bell McCormick • 20 words • 0.0% coverageEmily Bell McCormick • 23 words • 0.0% coverageWriter's voice • 8 words • 100.0% coverageEmily Bell McCormick • 14 words • 0.0% coverageEmily Bell McCormick • 48 words • 100.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageTracy Miller • 22 words • 0.0% coverageTracy Miller • 12 words • 0.0% coverageTracy Miller • 17 words • 0.0% coverageTracy Miller • 19 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 8 words • 100.0% coverageVerona Mauga • 38 words • 0.0% coverageVerona Mauga • 21 words • 0.0% coverageVerona Mauga • 14 words • 0.0% coverageVerona Mauga • 13 words • 0.0% coverageVerona Mauga • 25 words • 0.0% coverageWriter's voice • 25 words • 100.0% coverageWriter's voice • 6 words • 100.0% coverageWriter's voice • 22 words • 0.0% coverageEmily Bell McCormick • 26 words • 100.0% coverageEmily Bell McCormick • 17 words • 100.0% coverageEmily Bell McCormick • 8 words • 100.0% coverage
Selected voice

Emily Bell McCormick

100%flagged-word coverage
250 attributed words58% of attributed speech98% writer coverage
0%27.5%55.0%Indoctrination+40.5 ptsWriter: 9.9%Emily Bell McCormick: 50.4%50.4%Attempt to Sell a Product -46.1 ptsWriter: 46.1%Emily Bell McCormick: 0.0%0.0%Biased Writer Voice-22.4 ptsWriter: 22.4%Emily Bell McCormick: 0.0%0.0%Quote-first Misdirection+10.8 ptsWriter: 0.0%Emily Bell McCormick: 10.8%10.8%

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.