Republican Senator Crumbles Fortune Cookies While Vowing to ‘Stop Communist China’ ⁠37%

By Kathryn Wilkens⁠41%

7/9/2026, 12:55:01 AM

BS Summary: This article contains 23 faulty reasoning types, including Appeal to Authority, Framing Effect, and Ambiguity (Equivocation), with Negativity Bias as the most egregious example at 28.1% saturation with 108 hits. Analysis detected 857 faulty-reasoning hits from 385 analyzed words, generating a BS Score of 43.8% and a BS Rank of ⁠37% (13,329 of 21,171 articles). This article is better (less manipulative) than 63.00% of the article peer group.

Screenshot via @VoteMarsha on X 
Sen. 
Marsha Blackburn (R-TN) smashed fortune cookies into crumbs while declaring she would “stop Communist China” in a video posted Wednesday on X as part of her Tennessee gubernatorial campaign . 
“How hard am I gonna crack down on China?” 
Blackburn said in the video, sitting in what looks to be a caricature of a Chinese restaurant, complete with takeout boxes and lanterns hanging from the ceiling. 
“Well, here’s a clue.” 
It doesn’t take a fortune cookie to figure it out… 
As your governor, I’ll continue to work with President Trump to STOP Communist China and PROTECT Tennessee land. pic.twitter.com/XHAJb3OOu1 
- Marsha Blackburn (@VoteMarsha) July 8, 2026 
She then proceeded to crumble up multiple cookies with her hands, letting the crumbs fall on the table while staring into the camera. 
A narrator’s voice read, “Marsha Blackburn worked with President [ Donald ] Trump to take on Communist China. 
As governor, Marsha will fight to protect Tennessee land from Chinese front companies, close loopholes, and hunt down every Communist who tries to defy us.” 
“It doesn’t take a fortune cookie to figure it out,” Blackburn concluded. 
“Here in Tennessee, we’re gonna stop Communist China and protect Tennessee land.” 
The video ended with what sounded like a gong and an image of a maneki-neko—the “beckoning cat” figurine commonly sold in Chinatowns around the world, despite its Japanese origins . 
Not to mention, despite their association with Chinese restaurants in the United States, fortune cookies are widely believed to have originated in California, not China. 
While their exact history remains disputed, many historians credit Japanese immigrant Makoto Hagiwara with popularizing the modern fortune cookie at San Francisco’s Japanese Tea Garden in the early 20th century. 
A competing claim from a Chinese-American baker in Los Angeles has persisted for decades, but a 1983 “Court of Historical Review” in San Francisco symbolically ruled in Hagiwara’s favor . 
Importantly, Trump has maintained that he won’t make an endorsement in the state’s Republican gubernatorial primary between Blackburn and Rep. 
John Rose (R-TN), despite more than $1 million in new PAC ads featuring clips of the president praising her. 
The post Republican Senator Crumbles Fortune Cookies While Vowing to ‘Stop Communist China’ first appeared on Mediaite . 
Article reasoning-pattern comparisonThis article: 10.1%Kathryn Wilkens: 4.1%Mediaite: 5.0%Confirmation Bias10.1%This article: 0.0%Kathryn Wilkens: 0.9%Mediaite: 0.9%Anchoring Bias0.0%This article: 6.5%Kathryn Wilkens: 4.6%Mediaite: 3.7%Availability Heuristic6.5%This article: 7.8%Kathryn Wilkens: 1.0%Mediaite: 1.0%Representativeness Heuristic7.8%This article: 0.0%Kathryn Wilkens: 0.2%Mediaite: 0.7%Hindsight Bias0.0%This article: 0.0%Kathryn Wilkens: 2.8%Mediaite: 2.0%Overconfidence Bias0.0%This article: 17.7%Kathryn Wilkens: 8.9%Mediaite: 9.1%Framing Effect17.7%This article: 0.0%Kathryn Wilkens: 0.5%Mediaite: 0.4%Loss Aversion0.0%This article: 0.0%Kathryn Wilkens: 0.8%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: 0.0%Kathryn Wilkens: 3.0%Mediaite: 1.6%Pessimism Bias0.0%This article: 28.1%Kathryn Wilkens: 12.0%Mediaite: 14.6%Negativity Bias28.1%This article: 0.0%Kathryn Wilkens: 0.4%Mediaite: 1.6%Self-Serving Bias0.0%This article: 0.0%Kathryn Wilkens: 1.3%Mediaite: 1.7%Fundamental Attribution Error0.0%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.3%Actor-Observer Bias0.0%This article: 3.1%Kathryn Wilkens: 1.7%Mediaite: 2.2%In-Group Bias3.1%This article: 6.5%Kathryn Wilkens: 1.9%Mediaite: 2.0%Out-Group Homogeneity Bias6.5%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: 7.8%Kathryn Wilkens: 1.7%Mediaite: 2.3%Recency Bias7.8%This article: 7.8%Kathryn Wilkens: 1.5%Mediaite: 0.6%Primacy Effect7.8%This article: 0.0%Kathryn Wilkens: 0.2%Mediaite: 0.1%Blind-Spot Bias0.0%This article: 0.0%Kathryn Wilkens: 0.6%Mediaite: 3.8%Ad Hominem0.0%This article: 0.0%Kathryn Wilkens: 0.1%Mediaite: 1.2%Straw Man0.0%This article: 20.3%Kathryn Wilkens: 5.3%Mediaite: 3.6%Appeal to Authority20.3%This article: 14.5%Kathryn Wilkens: 2.2%Mediaite: 2.4%False Dilemma14.5%This article: 0.0%Kathryn Wilkens: 0.6%Mediaite: 1.3%Slippery Slope0.0%This article: 4.7%Kathryn Wilkens: 0.3%Mediaite: 0.3%Circular Reasoning4.7%This article: 6.5%Kathryn Wilkens: 9.6%Mediaite: 7.5%Hasty Generalization6.5%This article: 0.0%Kathryn Wilkens: 0.4%Mediaite: 0.4%Red Herring0.0%This article: 0.0%Kathryn Wilkens: 0.3%Mediaite: 0.8%Bandwagon0.0%This article: 5.5%Kathryn Wilkens: 5.6%Mediaite: 6.7%Appeal to Emotion5.5%This article: 5.7%Kathryn Wilkens: 1.2%Mediaite: 1.6%Begging the Question5.7%This article: 4.9%Kathryn Wilkens: 2.4%Mediaite: 2.9%Post Hoc (False Cause)4.9%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.1%Tu Quoque0.0%This article: 9.6%Kathryn Wilkens: 0.8%Mediaite: 1.2%Burden of Proof9.6%This article: 6.5%Kathryn Wilkens: 0.4%Mediaite: 0.1%Appeal to Nature6.5%This article: 0.0%Kathryn Wilkens: 0.3%Mediaite: 0.3%Composition/Division0.0%This article: 0.0%Kathryn Wilkens: 2.0%Mediaite: 2.8%Anecdotal0.0%This article: 0.0%Kathryn Wilkens: 0.0%Mediaite: 0.1%No True Scotsman0.0%This article: 15.6%Kathryn Wilkens: 3.0%Mediaite: 2.7%Ambiguity (Equivocation)15.6%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: 2.3%Kathryn Wilkens: 4.1%Mediaite: 3.3%Unattributed Quote2.3%This article: 6.0%Kathryn Wilkens: 4.5%Mediaite: 3.2%Quote-first Misdirection6.0%This article: 10.6%Kathryn Wilkens: 3.6%Mediaite: 8.3%Biased Writer Voice10.6%This article: 14.5%Kathryn Wilkens: 1.7%Mediaite: 1.6%Indoctrination14.5%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: 1.2%Politically Right Leaning Bias0.0%This article: 0.0%Kathryn Wilkens: 0.6%Mediaite: 1.4%Attempt to Sell a Product or S…0.0%

385 words analyzed.

Speakers

2speakers41%attributed speech226writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 11 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageMarsha Blackburn • 30 words • 100.0% coverageMarsha Blackburn • 9 words • 100.0% coverageMarsha Blackburn • 27 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageMarsha Blackburn • 19 words • 100.0% coverageMarsha Blackburn • 7 words • 0.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 18 words • 0.0% coverageMarsha Blackburn • 25 words • 100.0% coverageMarsha Blackburn • 12 words • 0.0% coverageMarsha Blackburn • 12 words • 100.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageMediaite • 18 words • 0.0% coverage
Selected voice

Marsha Blackburn

95%flagged-word coverage
141 attributed words89% of attributed speech96% writer coverage
0%20.0%40.0%Indoctrination+39.7 ptsWriter: 0.0%Marsha Blackburn: 39.7%39.7%Biased Writer Voice+16.4 ptsWriter: 4.9%Marsha Blackburn: 21.3%21.3%Quote-first Misdirection-10.2 ptsWriter: 10.2%Marsha Blackburn: 0.0%0.0%Unattributed Quote+6.4 ptsWriter: 0.0%Marsha Blackburn: 6.4%6.4%

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.