Mediaite82%

Kamala Harris Reveals Her Master Plan for Democrats to Beat ‘Cheating’ Republicans: ‘This Is Going To Be Controversial…’ 5%

By Sean James82%

8/2/2026, 5:40:25 PM

BS Summary: This article contains 10 faulty reasoning types, including Hasty Generalization, Begging the Question, and Hindsight Bias, with Framing Effect as the most egregious example at 21.6% saturation with 88 hits. Analysis detected 294 faulty-reasoning hits from 407 analyzed words, generating a BS Score of 14.5% and a BS Rank of 5% (24,210 of 25,257 articles). This article is better (less manipulative) than 95.90% of the article peer group.

It might be time to ditch the the Electoral College, according to Kamala Harris . 
The ex-vice president floated the idea as one of her suggestions for her fellow Democrats, if they want to beat the “ruthless” Republicans in the 2026 midterms and the 2028 presidential election. 
Harris dished her three-pronged plan for Dems while speaking at the National Urban League Conference on July 31 in Nashville. 
She said Dems have no choice but to consider radical ideas as a way to counter “cheating” by the GOP. 
“I know this is going to be controversial coming from me in particular  we need to revisit the Electoral College,” Harris said. 
The idea drew a few claps from the crowd. 
“We need to revisit the point of expanding the court to 13 justices like we have 13 district courts,” she continued. 
“We need to revisit, if they so want, statehood for Puerto Rico and D.C.” 
Harris , of course, was talking about adding four judges to the U.S. 
Supreme Court. 
Former President Joe Biden was the last commander-in-chief to pick a Supreme Court justice back in 2022, when Ketanji Brown Jackson was appointed. 
Her recommendation Dems need to “revisit” the Electoral College comes two years after she lost it 312-226 to President Donald Trump . 
The president received about 77.3 million votes in 2024  which was a shade less than 50% of the votes  on his way to winning 31 states, while Harris earned roughly 75 million votes. 
Harris on Friday ripped one of Trump’s ’24 slogans as a way to drive home her point about drastic changes. 
“In light of and in this environment where they are cheating, we will be too big to rig. 
Too big to rig,” she said. 
“It means being ruthless  they are ruthless! 
We need to be ruthless too.” 
Harris continued, “and by that, I do not mean cruel. 
That is not our nature. 
By that I do not mean breaking the law. 
That is not what we do. 
But I do mean we must be uncompromising, and we must allow for a real conversation about revisiting certain things.” 
Watch above via Fox Nashville on YouTube. 
The post Kamala Harris Reveals Her Master Plan for Democrats to Beat ‘Cheating’ Republicans: ‘This Is Going To Be Controversial…’ first appeared on Mediaite . 
Confirmation Bias
0%
Anchoring Bias
0%
Availability Heuristic
0%
Representativeness Heuristic
0%
Hindsight Bias
5.4%
Overconfidence Bias
0%
Framing Effect
21.6%
Loss Aversion
0%
Status Quo Bias
0%
Sunk Cost Effect
0%
Optimism Bias
0%
Pessimism Bias
0%
Negativity Bias
4.4%
Self-Serving Bias
5.4%
Fundamental Attribution Error
0%
Actor-Observer Bias
0%
In-Group Bias
2%
Out-Group Homogeneity Bias
0%
Halo Effect
0%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
0%
Primacy Effect
0%
Blind-Spot Bias
0%
Ad Hominem
0%
Straw Man
0%
Appeal to Authority
0%
False Dilemma
0%
Slippery Slope
0%
Circular Reasoning
0%
Hasty Generalization
9.8%
Red Herring
0%
Bandwagon
0%
Appeal to Emotion
0%
Begging the Question
9.3%
Post Hoc (False Cause)
0%
Tu Quoque
5.4%
Burden of Proof
0%
Appeal to Nature
0%
Composition/Division
0%
Anecdotal
0%
No True Scotsman
0%
Ambiguity (Equivocation)
0%
Gambler’s Fallacy
0%
Middle Ground
0%
Personal Incredulity
0%
Special Pleading
0%
Genetic Fallacy
0%
Unattributed Quote
0%
Quote-first Misdirection
4.4%
Biased Writer Voice
4.4%
Indoctrination
0%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
0%
Attempt to Sell a Product or Service
0%

407 words analyzed.

Analysis

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