Mediaite⁠70%

Fox’s Leslie Marshall Says Trump’s Multibillion-Dollar Haul Last Year Shows Just ‘How Tone Deaf’ He Is ⁠42%

By Kathryn Wilkens⁠41%

7/3/2026, 12:50:14 AM

BS Summary: This article contains 19 faulty reasoning types, including Framing Effect, Hasty Generalization, and Pessimism Bias, with Negativity Bias as the most egregious example at 43.1% saturation with 149 hits. Analysis detected 812 faulty-reasoning hits from 346 analyzed words, generating a BS Score of 46.1% and a BS Rank of ⁠42% (12,758 of 21,886 articles). This article is better (less manipulative) than 58.30% of the article peer group.

Fox News contributor Leslie Marshall said that President Donald Trump's reported $1.4 billion in cryptocurrency profits show just "how tone deaf" he is during Thursday's edition of Special Report. 
The president’s 2025 financial disclosure report, released earlier this week, revealed he brought in more than $1 billion from his family’s cryptocurrency ventures. 
The filing reported roughly $500 million in income from World Liberty Financial, the crypto company founded with his sons Eric Trump, Donald Trump Jr., and Barron Trump, along with approximately $635 million from sales of the $TRUMP meme coin through CIC Digital LLC. 
The disclosure also detailed hundreds of millions of dollars in income from Trump’s real estate holdings and millions more from licensing deals and other business ventures. 
The president made more than $2 billion overall. 
As Fox News host Bret Baier pointed out, if the Democrats win the upcoming midterm elections, the profits will be "ripe territory" for congressional investigations. 
"We're seeing a lot of the MAGA base turning on the president with this," added Marshall. 
"They're saying, 'Look, he really doesn't care about us. 
He's getting richer, I'm getting poorer. 
I thought, you know, we elected him because he was gonna make life better for us.' 
And better for the American people, whether they're a Democrat or a Republican, whether they supported Donald Trump or not, is a more affordable life, and that's just not what's going to happen." 
Baier went on to ask whether Marshall believes instances like these are "in part fueling some of the populism in the Democratic socialist movement." 
She replied: 
Yeah, and I think that's one of the reasons it's successful, and I think, also, it just speaks to again, and I'm sorry to say it again, how tone deaf this president and this administration is to the American people. 
The American people look and say, "Look, this guy is profiting as president. 
That is not what I elected him to do." 
Watch the full clip above via Fox News. 
Article reasoning-pattern comparisonThis article: 14.2%Kathryn Wilkens: 4.2%Mediaite: 5.0%Confirmation Bias14.2%This article: 2.3%Kathryn Wilkens: 0.8%Mediaite: 0.9%Anchoring Bias2.3%This article: 4.6%Kathryn Wilkens: 4.7%Mediaite: 3.8%Availability Heuristic4.6%This article: 0.0%Kathryn Wilkens: 0.9%Mediaite: 1.0%Representativeness Heuristic0.0%This article: 0.0%Kathryn Wilkens: 0.2%Mediaite: 0.7%Hindsight Bias0.0%This article: 0.0%Kathryn Wilkens: 3.3%Mediaite: 2.1%Overconfidence Bias0.0%This article: 27.2%Kathryn Wilkens: 8.9%Mediaite: 9.1%Framing Effect27.2%This article: 1.7%Kathryn Wilkens: 0.4%Mediaite: 0.4%Loss Aversion1.7%This article: 0.0%Kathryn Wilkens: 1.0%Mediaite: 0.4%Status Quo Bias0.0%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.1%Sunk Cost Effect0.0%This article: 0.0%Kathryn Wilkens: 0.3%Mediaite: 1.2%Optimism Bias0.0%This article: 16.2%Kathryn Wilkens: 2.9%Mediaite: 1.6%Pessimism Bias16.2%This article: 43.1%Kathryn Wilkens: 11.8%Mediaite: 14.7%Negativity Bias43.1%This article: 0.0%Kathryn Wilkens: 0.9%Mediaite: 1.6%Self-Serving Bias0.0%This article: 0.0%Kathryn Wilkens: 1.2%Mediaite: 1.7%Fundamental Attribution Error0.0%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.3%Actor-Observer Bias0.0%This article: 13.3%Kathryn Wilkens: 1.6%Mediaite: 2.1%In-Group Bias13.3%This article: 0.0%Kathryn Wilkens: 1.8%Mediaite: 2.0%Out-Group Homogeneity Bias0.0%This article: 0.0%Kathryn Wilkens: 0.1%Mediaite: 1.3%Halo Effect0.0%This article: 0.0%Kathryn Wilkens: 0.4%Mediaite: 0.7%Horn Effect0.0%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.1%Dunning-Kruger Effect0.0%This article: 0.0%Kathryn Wilkens: 1.8%Mediaite: 2.3%Recency Bias0.0%This article: 0.0%Kathryn Wilkens: 1.4%Mediaite: 0.6%Primacy Effect0.0%This article: 0.0%Kathryn Wilkens: 0.2%Mediaite: 0.1%Blind-Spot Bias0.0%This article: 0.0%Kathryn Wilkens: 0.5%Mediaite: 3.8%Ad Hominem0.0%This article: 0.0%Kathryn Wilkens: 0.1%Mediaite: 1.2%Straw Man0.0%This article: 0.0%Kathryn Wilkens: 5.2%Mediaite: 3.5%Appeal to Authority0.0%This article: 7.2%Kathryn Wilkens: 2.2%Mediaite: 2.4%False Dilemma7.2%This article: 0.0%Kathryn Wilkens: 0.6%Mediaite: 1.3%Slippery Slope0.0%This article: 0.0%Kathryn Wilkens: 0.3%Mediaite: 0.3%Circular Reasoning0.0%This article: 17.9%Kathryn Wilkens: 9.5%Mediaite: 7.6%Hasty Generalization17.9%This article: 6.9%Kathryn Wilkens: 0.6%Mediaite: 0.4%Red Herring6.9%This article: 0.0%Kathryn Wilkens: 0.3%Mediaite: 0.9%Bandwagon0.0%This article: 0.0%Kathryn Wilkens: 5.3%Mediaite: 6.6%Appeal to Emotion0.0%This article: 11.6%Kathryn Wilkens: 1.3%Mediaite: 1.6%Begging the Question11.6%This article: 0.0%Kathryn Wilkens: 2.3%Mediaite: 2.9%Post Hoc (False Cause)0.0%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.1%Tu Quoque0.0%This article: 0.0%Kathryn Wilkens: 0.9%Mediaite: 1.2%Burden of Proof0.0%This article: 0.0%Kathryn Wilkens: 0.3%Mediaite: 0.1%Appeal to Nature0.0%This article: 0.0%Kathryn Wilkens: 0.3%Mediaite: 0.3%Composition/Division0.0%This article: 7.2%Kathryn Wilkens: 2.0%Mediaite: 3.0%Anecdotal7.2%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.1%No True Scotsman0.0%This article: 9.5%Kathryn Wilkens: 3.0%Mediaite: 2.8%Ambiguity (Equivocation)9.5%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.1%Middle Ground0.0%This article: 0.0%Kathryn Wilkens: 0.5%Mediaite: 0.3%Personal Incredulity0.0%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.1%Special Pleading0.0%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.6%Genetic Fallacy0.0%This article: 15.3%Kathryn Wilkens: 4.2%Mediaite: 3.3%Unattributed Quote15.3%This article: 8.4%Kathryn Wilkens: 4.5%Mediaite: 3.2%Quote-first Misdirection8.4%This article: 16.2%Kathryn Wilkens: 3.5%Mediaite: 8.3%Biased Writer Voice16.2%This article: 9.5%Kathryn Wilkens: 1.6%Mediaite: 1.6%Indoctrination9.5%This article: 0.0%Kathryn Wilkens: 0.9%Mediaite: 2.0%Politically Left Leaning Bias0.0%This article: 0.0%Kathryn Wilkens: 0.2%Mediaite: 1.1%Politically Right Leaning Bias0.0%This article: 2.3%Kathryn Wilkens: 0.6%Mediaite: 1.4%Attempt to Sell a Product or S…2.3%

346 words analyzed.

Speakers

3speakers66%attributed speech118writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 16 words • 100.0% coverageLeslie Marshall • 29 words • 100.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 43 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageBret Baier • 25 words • 0.0% coverageLeslie Marshall • 16 words • 0.0% coverageLeslie Marshall • 9 words • 100.0% coverageLeslie Marshall • 6 words • 100.0% coverageLeslie Marshall • 16 words • 100.0% coverageLeslie Marshall • 33 words • 100.0% coverageBret Baier • 24 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageLeslie Marshall • 40 words • 100.0% coverageLeslie Marshall • 13 words • 100.0% coverageLeslie Marshall • 9 words • 100.0% coverageFox News • 8 words • 100.0% coverage
Selected voice

Leslie Marshall

100%flagged-word coverage
171 attributed words75% of attributed speech20% writer coverage
0%17.5%35.0%Unattributed Quote+31.0 ptsWriter: 0.0%Leslie Marshall: 31.0%31.0%Biased Writer Voice+9.8 ptsWriter: 13.6%Leslie Marshall: 23.4%23.4%Indoctrination+19.3 ptsWriter: 0.0%Leslie Marshall: 19.3%19.3%Quote-first Misdirection+17.0 ptsWriter: 0.0%Leslie Marshall: 17.0%17.0%

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.