Gavin Newsom’s balancing act on taxing the rich 34%

By Lynn La25%

7/22/2026, 1:00:00 PM

BS Summary: This article contains 22 faulty reasoning types, including Post Hoc (False Cause), Availability Heuristic, and Representativeness Heuristic, with Fundamental Attribution Error as the most egregious example at 10.3% saturation with 97 hits. Analysis detected 895 faulty-reasoning hits from 940 analyzed words, generating a BS Score of 41.8% and a BS Rank of 34% (14,581 of 21,887 articles). This article is better (less manipulative) than 66.60% of the article peer group.

Gov. 
Gavin Newsom speaks during a press conference in Hayward on March 2, 2026. 
Photo by Manuel Orbegozo for CalMatters 
Gov. 
Gavin Newsom knows that many Democrats across the country want to “eat the rich” with wealth taxes. 
But he can’t bring himself to stomach the meal when it comes to a November California ballot proposal that would do just that . 
What’s a guy who wants to run for president in 2028 to do? 
Over the past few weeks, Newsom has been appealing to populist messaging by focusing on voters’ economic anxieties, wealth inequality and artificial intelligence-driven job losses, writes CalMatters’ Jeanne Kuang. 
He’s also calling for a nationwide wealth tax on anyone making more than $100 million, which might capture the Democratic zeitgeist without prompting more California billionaires to move to, say, Austin. 
Newsom , in a statement : “The system the American founders built was designed to prevent the concentration of power in a few hands. 
But we’ve allowed that concentration to happen anyway, slowly and in plain sight. 
 It’s time to democratize the American economy to save our democracy.” 
But when it comes to a billionaire tax in California, Newsom is against it. 
The governor pressured the healthcare union behind the proposal to drop the measure in exchange for concessions, but failed. 
He  along with other Democratic allies and Planned Parenthood  argues that billionaires could simply move their assets to another state. 
This needle threading is Newsom’s attempt at “balancing two pressures,” said Kevin Liao, a Democratic strategist. 
Liao: “There’s a desire to meet the demands of his constituents and the current appetite to be against billionaires  (and) the cold political reality that much of his career and presumably his future ambitions have also been built on the financial support from a lot of wealthy folks in Silicon Valley.” 
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Photo by Miguel Vasconcellos for CalMatters 
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By owning the facilities, the federal government would be able to lock out local governments and the state from oversight and access. 
Myth busting your insurance 
A fireplace remains standing from a home that was burned down by the Eaton Fire in the Altadena and Pasadena area on Jan. 
8, 2025. 
Photo by Jules Hotz for CalMatters 
As California voters gear up to vote for a new insurance commissioner in November, CalMatters’ Levi Sumagaysay takes a look at four common misconceptions people have about insurance and the various issues plaguing the state’s insurance market. 
One of the top myths people have is that California’s insurance issues only affect homeowners and the well-to-do  not the estimated 44% of the state who don’t own their homes. 
But rising insurance costs affect this population too, with some landlords reporting to CalMatters that they have passed some of those costs to renters. 
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Armed robots are on the horizon , as Silicon Valley pitches new military tech // The Washington Post (gift link) 
Article reasoning-pattern comparisonThis article: 0.0%Lynn La: 1.4%CalMatters: 2.5%Confirmation Bias0.0%This article: 0.0%Lynn La: 0.6%CalMatters: 0.9%Anchoring Bias0.0%This article: 7.8%Lynn La: 2.7%CalMatters: 2.4%Availability Heuristic7.8%This article: 7.8%Lynn La: 0.7%CalMatters: 1.0%Representativeness Heuristic7.8%This article: 0.0%Lynn La: 0.2%CalMatters: 0.4%Hindsight Bias0.0%This article: 0.5%Lynn La: 0.3%CalMatters: 0.8%Overconfidence Bias0.5%This article: 0.0%Lynn La: 6.4%CalMatters: 5.7%Framing Effect0.0%This article: 0.0%Lynn La: 0.9%CalMatters: 0.8%Loss Aversion0.0%This article: 0.0%Lynn La: 0.6%CalMatters: 0.6%Status Quo Bias0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.2%Sunk Cost Effect0.0%This article: 0.0%Lynn La: 1.2%CalMatters: 1.9%Optimism Bias0.0%This article: 3.3%Lynn La: 1.7%CalMatters: 2.0%Pessimism Bias3.3%This article: 6.3%Lynn La: 9.0%CalMatters: 8.0%Negativity Bias6.3%This article: 2.0%Lynn La: 1.9%CalMatters: 1.6%Self-Serving Bias2.0%This article: 10.3%Lynn La: 1.2%CalMatters: 1.0%Fundamental Attribution Error10.3%This article: 0.0%Lynn La: 0.1%CalMatters: 0.2%Actor-Observer Bias0.0%This article: 1.8%Lynn La: 1.1%CalMatters: 0.8%In-Group Bias1.8%This article: 0.0%Lynn La: 0.5%CalMatters: 0.3%Out-Group Homogeneity Bias0.0%This article: 0.0%Lynn La: 0.8%CalMatters: 1.4%Halo Effect0.0%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Horn Effect0.0%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Lynn La: 0.6%CalMatters: 1.1%Recency Bias0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.2%Primacy Effect0.0%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Blind-Spot Bias0.0%This article: 5.5%Lynn La: 0.9%CalMatters: 0.6%Ad Hominem5.5%This article: 0.0%Lynn La: 0.2%CalMatters: 0.3%Straw Man0.0%This article: 3.3%Lynn La: 3.7%CalMatters: 3.2%Appeal to Authority3.3%This article: 4.9%Lynn La: 1.1%CalMatters: 1.0%False Dilemma4.9%This article: 4.8%Lynn La: 0.8%CalMatters: 1.3%Slippery Slope4.8%This article: 0.0%Lynn La: 0.0%CalMatters: 0.1%Circular Reasoning0.0%This article: 3.4%Lynn La: 3.7%CalMatters: 3.7%Hasty Generalization3.4%This article: 0.0%Lynn La: 0.1%CalMatters: 0.1%Red Herring0.0%This article: 0.0%Lynn La: 0.5%CalMatters: 0.4%Bandwagon0.0%This article: 1.4%Lynn La: 6.6%CalMatters: 5.3%Appeal to Emotion1.4%This article: 2.7%Lynn La: 0.8%CalMatters: 0.8%Begging the Question2.7%This article: 8.0%Lynn La: 2.1%CalMatters: 2.7%Post Hoc (False Cause)8.0%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Tu Quoque0.0%This article: 0.0%Lynn La: 0.0%CalMatters: 0.4%Burden of Proof0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.2%Appeal to Nature0.0%This article: 0.0%Lynn La: 0.1%CalMatters: 0.2%Composition/Division0.0%This article: 5.9%Lynn La: 2.1%CalMatters: 1.8%Anecdotal5.9%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%No True Scotsman0.0%This article: 2.6%Lynn La: 1.2%CalMatters: 1.2%Ambiguity (Equivocation)2.6%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.1%Middle Ground0.0%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Personal Incredulity0.0%This article: 2.0%Lynn La: 0.2%CalMatters: 0.3%Special Pleading2.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.1%Genetic Fallacy0.0%This article: 4.9%Lynn La: 2.2%CalMatters: 0.9%Unattributed Quote4.9%This article: 2.6%Lynn La: 1.6%CalMatters: 0.7%Quote-first Misdirection2.6%This article: 0.0%Lynn La: 4.2%CalMatters: 3.3%Biased Writer Voice0.0%This article: 0.0%Lynn La: 2.0%CalMatters: 1.0%Indoctrination0.0%This article: 0.0%Lynn La: 0.7%CalMatters: 0.6%Politically Left Leaning Bias0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.2%Politically Right Leaning Bias0.0%This article: 3.6%Lynn La: 3.7%CalMatters: 1.0%Attempt to Sell a Product or S…3.6%

940 words analyzed.

Speakers

4speakers18%attributed speech769writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 8 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 24 words • 100.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 19 words • 0.0% coveragePlanned Parenthood • 22 words • 100.0% coverageWriter's voice • 16 words • 0.0% coverageKevin Liao • 52 words • 0.0% coverageWriter's voice • 25 words • 100.0% coverageWriter's voice • 9 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 36 words • 0.0% coverageImmigration and Customs Enforcement • 25 words • 0.0% coverageImmigration and Customs Enforcement • 27 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 37 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 31 words • 0.0% coveragePaloma Esquivel • 45 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverage
Selected voice

Kevin Liao

100%flagged-word coverage
52 attributed words30% of attributed speech58% writer coverage
0%2.5%5.0%Attempt to Sell a Product -4.4 ptsWriter: 4.4%Kevin Liao: 0.0%0.0%Unattributed Quote-3.1 ptsWriter: 3.1%Kevin Liao: 0.0%0.0%Quote-first Misdirection-3.1 ptsWriter: 3.1%Kevin Liao: 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.