GOP Rep Mercilessly Booed At Town Hall While Defending Signature Trump Policy ⁠85%

By Anthony Orrico⁠0%

7/8/2026, 9:03:05 AM

BS Summary: This article contains 15 faulty reasoning types, including Biased Writer Voice, Appeal to Emotion, and Framing Effect, with Negativity Bias as the most egregious example at 81.3% saturation with 113 hits. Analysis detected 546 faulty-reasoning hits from 139 analyzed words, generating a BS Score of 77.7% and a BS Rank of ⁠85% (3,061 of 20,409 articles). This article is worse (more manipulative) than 85.00% of the article peer group.

Rep. 
Mike Flood (R-Neb.) was greeted with a chorus of boos during a town hall event on Tuesday after defending President Donald Trump’s “One Big Beautiful Bill Act” 
Flood was asked what he planned to do about the legislation’s cuts to disability benefits. 
Trump’s signature legislation slashed over $1 trillion over the next decade from Medicaid, the primary source of funding for those benefits. 
Flood’s been heckled numerous times since last July over the passage of the “One Big Beautiful Bill Act.” 
“I’d ask you please not to refer to that monstrosity as the ‘big, beautiful bill,’” one voter requested, to loud cheers, at the event in Lincoln, Neb. that was aired live by PBS last August. 
**Watch Flood’s full remarks from Tuesday’s town hall here: ** 
Article reasoning-pattern comparisonThis article: 7.2%Anthony Orrico: 3.1%AP: 3.2%Confirmation Bias7.2%This article: 0.0%Anthony Orrico: 0.0%AP: 0.8%Anchoring Bias0.0%This article: 0.0%Anthony Orrico: 8.5%AP: 2.8%Availability Heuristic0.0%This article: 0.0%Anthony Orrico: 1.9%AP: 1.1%Representativeness Heuristic0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.5%Hindsight Bias0.0%This article: 0.0%Anthony Orrico: 1.0%AP: 1.4%Overconfidence Bias0.0%This article: 43.2%Anthony Orrico: 20.0%AP: 9.9%Framing Effect43.2%This article: 15.1%Anthony Orrico: 1.0%AP: 0.4%Loss Aversion15.1%This article: 0.0%Anthony Orrico: 0.0%AP: 0.3%Status Quo Bias0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.1%Sunk Cost Effect0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 1.4%Optimism Bias0.0%This article: 0.0%Anthony Orrico: 4.1%AP: 2.4%Pessimism Bias0.0%This article: 81.3%Anthony Orrico: 12.4%AP: 13.5%Negativity Bias81.3%This article: 0.0%Anthony Orrico: 0.0%AP: 1.8%Self-Serving Bias0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 1.5%Fundamental Attribution Error0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.2%Actor-Observer Bias0.0%This article: 0.0%Anthony Orrico: 1.9%AP: 2.2%In-Group Bias0.0%This article: 0.0%Anthony Orrico: 9.7%AP: 1.3%Out-Group Homogeneity Bias0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 1.4%Halo Effect0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.7%Horn Effect0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.0%Dunning-Kruger Effect0.0%This article: 12.9%Anthony Orrico: 3.6%AP: 1.5%Recency Bias12.9%This article: 25.2%Anthony Orrico: 1.6%AP: 0.2%Primacy Effect25.2%This article: 0.0%Anthony Orrico: 0.0%AP: 0.0%Blind-Spot Bias0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 2.9%Ad Hominem0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 1.0%Straw Man0.0%This article: 0.0%Anthony Orrico: 0.7%AP: 2.6%Appeal to Authority0.0%This article: 0.0%Anthony Orrico: 4.1%AP: 1.9%False Dilemma0.0%This article: 0.0%Anthony Orrico: 8.3%AP: 2.0%Slippery Slope0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.2%Circular Reasoning0.0%This article: 12.9%Anthony Orrico: 21.4%AP: 6.5%Hasty Generalization12.9%This article: 0.0%Anthony Orrico: 0.0%AP: 0.4%Red Herring0.0%This article: 0.0%Anthony Orrico: 3.3%AP: 0.5%Bandwagon0.0%This article: 44.6%Anthony Orrico: 19.9%AP: 6.2%Appeal to Emotion44.6%This article: 0.0%Anthony Orrico: 1.8%AP: 1.3%Begging the Question0.0%This article: 0.0%Anthony Orrico: 5.6%AP: 2.6%Post Hoc (False Cause)0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.1%Tu Quoque0.0%This article: 10.8%Anthony Orrico: 0.7%AP: 0.6%Burden of Proof10.8%This article: 0.0%Anthony Orrico: 0.0%AP: 0.2%Appeal to Nature0.0%This article: 0.0%Anthony Orrico: 1.4%AP: 0.1%Composition/Division0.0%This article: 25.2%Anthony Orrico: 1.6%AP: 1.3%Anecdotal25.2%This article: 0.0%Anthony Orrico: 1.0%AP: 0.2%No True Scotsman0.0%This article: 0.0%Anthony Orrico: 3.4%AP: 1.9%Ambiguity (Equivocation)0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.1%Middle Ground0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.0%Personal Incredulity0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.1%Special Pleading0.0%This article: 0.0%Anthony Orrico: 0.0%AP: 0.3%Genetic Fallacy0.0%This article: 25.2%Anthony Orrico: 7.5%AP: 2.7%Unattributed Quote25.2%This article: 25.2%Anthony Orrico: 3.3%AP: 2.0%Quote-first Misdirection25.2%This article: 48.2%Anthony Orrico: 18.6%AP: 12.7%Biased Writer Voice48.2%This article: 0.0%Anthony Orrico: 0.0%AP: 1.6%Indoctrination0.0%This article: 0.0%Anthony Orrico: 16.6%AP: 4.6%Politically Left Leaning Bias0.0%This article: 8.6%Anthony Orrico: 0.6%AP: 0.3%Politically Right Leaning Bias8.6%This article: 7.2%Anthony Orrico: 0.5%AP: 0.3%Attempt to Sell a Product or S…7.2%

139 words analyzed.

Speakers

1speaker43%attributed speech79writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 100.0% coverageWriter's voice • 1 words • 0.0% coverageMike Flood • 27 words • 100.0% coverageMike Flood • 15 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageMike Flood • 18 words • 100.0% coverageWriter's voice • 35 words • 100.0% coverageWriter's voice • 10 words • 100.0% coverage
Selected voice

Mike Flood

100%flagged-word coverage
60 attributed words100% of attributed speech99% writer coverage
0%37.5%75.0%Biased Writer Voice+47.2 ptsWriter: 27.8%Mike Flood: 75.0%75.0%Unattributed Quote-44.3 ptsWriter: 44.3%Mike Flood: 0.0%0.0%Quote-first Misdirection-44.3 ptsWriter: 44.3%Mike Flood: 0.0%0.0%Politically Right Leaning -15.2 ptsWriter: 15.2%Mike Flood: 0.0%0.0%Attempt to Sell a Product -12.7 ptsWriter: 12.7%Mike Flood: 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.