New presidential poll shows Gavin Newsom, Kamala Harris in dead heat as report on 2024 run exposes party failures ⁠60%

By Daniel Farr⁠69%

5/21/2026, 9:46:50 PM

BS Summary: This article contains 26 faulty reasoning types, including Biased Writer Voice, Post Hoc (False Cause), and Ambiguity (Equivocation), with Negativity Bias as the most egregious example at 57.1% saturation with 313 hits. Analysis detected 1,594 faulty-reasoning hits from 548 analyzed words, generating a BS Score of 56.1% and a BS Rank of ⁠60% (8,793 of 21,887 articles). This article is worse (more manipulative) than 59.80% of the article peer group.

After President Trump’s crushing 2024 victory sent Democrats into panic mode, a new 2028 primary poll out this week shows the party rallying around two familiar, and deeply polarizing, figures: Kamala Harris and California Gov. 
Gavin Newsom. 
The nationwide survey of 800 likely Democrat primary voters, conducted by Lake Research Partners from May 6-11, tested 13 potential Democratic contenders using a ranked choice voting simulation. 
In the final ranked-choice matchup, failed 2024 presidential candidate Harris narrowly beat presumed presidential candidate Newsom 52% to 48%, through the result fell within the poll’s margin of error. 
But the topline numbers revealed a party still fractured and struggling to generate real enthusiasm after Trump became the first Republican nominee in 20 years to win the popular vote while steamrolling Democrats in the Electoral College. 
Only 26% of respondents ranked Harris as their first choice. 
Newsom drew just 17%. 
Rather than producing a fresh breakout star, Democrats appear stuck recycling the same national figures tied to the chaos and failures of the Biden era. 
The ranked choice system helped rescue both candidates by allowing them to pick up second- and third-choice support from eliminated rivals. 
Only 43% of voters initially picked Harris or Newsom first, but 80% ranked one or both somewhere in their top five choices, keeping their ballots active in later rounds. 
Supporters of Rep. 
Alexandria Ocasio-Cortez were more likely to back Harris as a fallback option, while voters supporting Pete Buttigieg, Sen. 
Mark Kelly, Pennsylvania Gov. 
Josh Shapiro and Sen. 
Cory Booker leaned more toward Newsom. 
Newsom has also increasingly adopted a more aggressive online style that mirrors Trump’s social media approach, a striking shift for liberals after years spent attacking Trump’s political tactics.. 
The poll found strong Democratic support for ranked choice voting itself, with 63% backing its use in the 2028 presidential primary. 
Support rose to 70% after voters completed the exercise, and 84% said ranking candidates was easy. 
The poll landed alongside a brutal Democratic National Committee “autopsy” released Thursday that detailed how badly Republicans outmaneuvered Democrats in 2024. 
The draft report, written by former Bill Clinton strategist Paul Rivera, blasted Democrats for relying too heavily on “negative partisanship” to win races. 
The autopsy also blamed allies of former President Joe Biden for failing to properly prepare Harris after Biden abandoned his reelection campaign in July 2024. 
According to the report, the White House requested polling before the 2022 midterms on “how Dr. 
[Jill] Biden could support her husband as president,” while “no similar research was conducted to support the Vice President.” 
The report also admitted Democrats failed to effectively counter Republican attacks showing Harris as an ineffective “border czar” during Biden's immigration crisis. 
The report did acknowledge the effectiveness of one devastating Trump campaign ad targeting Democrats on transgender issues with the line: "Kamala is for they/them. 
President Trump is for you." 
In one of the sharpest admissions, Rivera concluded: “The GOP’s victory in 2024 largely came down to its ability to learn more from President [Barack] Obama’s victory [in 2008] than Democrats did.” 
The report found that Democrats failed to effectively counter Republican attacks showing Harris as an ineffective “border czar” during Biden's immigration crisis. 
Article reasoning-pattern comparisonThis article: 8.2%Daniel Farr: 3.8%California Post: 4.1%Confirmation Bias8.2%This article: 5.3%Daniel Farr: 1.3%California Post: 1.4%Anchoring Bias5.3%This article: 6.8%Daniel Farr: 4.7%California Post: 4.2%Availability Heuristic6.8%This article: 0.0%Daniel Farr: 1.1%California Post: 1.1%Representativeness Heuristic0.0%This article: 5.8%Daniel Farr: 0.6%California Post: 0.8%Hindsight Bias5.8%This article: 0.0%Daniel Farr: 0.5%California Post: 2.2%Overconfidence Bias0.0%This article: 8.8%Daniel Farr: 12.8%California Post: 10.3%Framing Effect8.8%This article: 0.0%Daniel Farr: 1.2%California Post: 0.9%Loss Aversion0.0%This article: 4.6%Daniel Farr: 0.9%California Post: 0.6%Status Quo Bias4.6%This article: 4.6%Daniel Farr: 0.1%California Post: 0.2%Sunk Cost Effect4.6%This article: 0.0%Daniel Farr: 1.4%California Post: 2.5%Optimism Bias0.0%This article: 4.6%Daniel Farr: 1.4%California Post: 1.5%Pessimism Bias4.6%This article: 57.1%Daniel Farr: 17.4%California Post: 16.0%Negativity Bias57.1%This article: 0.0%Daniel Farr: 0.9%California Post: 2.4%Self-Serving Bias0.0%This article: 9.7%Daniel Farr: 1.4%California Post: 1.5%Fundamental Attribution Error9.7%This article: 5.1%Daniel Farr: 0.2%California Post: 0.2%Actor-Observer Bias5.1%This article: 5.1%Daniel Farr: 0.9%California Post: 1.6%In-Group Bias5.1%This article: 0.0%Daniel Farr: 0.9%California Post: 1.1%Out-Group Homogeneity Bias0.0%This article: 0.0%Daniel Farr: 2.2%California Post: 3.1%Halo Effect0.0%This article: 0.0%Daniel Farr: 0.5%California Post: 0.6%Horn Effect0.0%This article: 0.0%Daniel Farr: 0.0%California Post: 0.0%Dunning-Kruger Effect0.0%This article: 10.2%Daniel Farr: 1.8%California Post: 1.6%Recency Bias10.2%This article: 2.9%Daniel Farr: 0.4%California Post: 0.5%Primacy Effect2.9%This article: 0.0%Daniel Farr: 0.0%California Post: 0.0%Blind-Spot Bias0.0%This article: 0.0%Daniel Farr: 2.2%California Post: 2.6%Ad Hominem0.0%This article: 0.0%Daniel Farr: 0.2%California Post: 0.5%Straw Man0.0%This article: 10.0%Daniel Farr: 3.0%California Post: 4.2%Appeal to Authority10.0%This article: 5.8%Daniel Farr: 1.5%California Post: 1.5%False Dilemma5.8%This article: 0.0%Daniel Farr: 0.7%California Post: 0.9%Slippery Slope0.0%This article: 0.0%Daniel Farr: 0.0%California Post: 0.2%Circular Reasoning0.0%This article: 10.9%Daniel Farr: 3.9%California Post: 5.5%Hasty Generalization10.9%This article: 0.0%Daniel Farr: 0.6%California Post: 0.7%Red Herring0.0%This article: 0.0%Daniel Farr: 0.5%California Post: 1.4%Bandwagon0.0%This article: 11.7%Daniel Farr: 8.2%California Post: 8.9%Appeal to Emotion11.7%This article: 0.0%Daniel Farr: 0.6%California Post: 1.1%Begging the Question0.0%This article: 23.5%Daniel Farr: 2.2%California Post: 2.7%Post Hoc (False Cause)23.5%This article: 0.0%Daniel Farr: 0.1%California Post: 0.2%Tu Quoque0.0%This article: 3.5%Daniel Farr: 0.8%California Post: 0.8%Burden of Proof3.5%This article: 0.0%Daniel Farr: 0.1%California Post: 0.2%Appeal to Nature0.0%This article: 0.0%Daniel Farr: 0.1%California Post: 0.2%Composition/Division0.0%This article: 0.0%Daniel Farr: 1.9%California Post: 3.6%Anecdotal0.0%This article: 0.0%Daniel Farr: 0.1%California Post: 0.0%No True Scotsman0.0%This article: 17.2%Daniel Farr: 1.6%California Post: 2.0%Ambiguity (Equivocation)17.2%This article: 0.0%Daniel Farr: 0.0%California Post: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Daniel Farr: 0.1%California Post: 0.1%Middle Ground0.0%This article: 0.0%Daniel Farr: 0.0%California Post: 0.1%Personal Incredulity0.0%This article: 0.0%Daniel Farr: 0.1%California Post: 0.2%Special Pleading0.0%This article: 0.0%Daniel Farr: 0.3%California Post: 0.4%Genetic Fallacy0.0%This article: 12.0%Daniel Farr: 2.6%California Post: 3.2%Unattributed Quote12.0%This article: 4.4%Daniel Farr: 1.8%California Post: 2.1%Quote-first Misdirection4.4%This article: 44.5%Daniel Farr: 12.2%California Post: 13.1%Biased Writer Voice44.5%This article: 0.0%Daniel Farr: 1.6%California Post: 1.4%Indoctrination0.0%This article: 4.6%Daniel Farr: 0.4%California Post: 0.4%Politically Left Leaning Bias4.6%This article: 4.0%Daniel Farr: 3.8%California Post: 3.0%Politically Right Leaning Bias4.0%This article: 0.0%Daniel Farr: 0.7%California Post: 6.0%Attempt to Sell a Product or S…0.0%

548 words analyzed.

Speakers

2speakers13%attributed speech475writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 19 words • 100.0% coverageWriter's voice • 35 words • 100.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 29 words • 100.0% coverageWriter's voice • 37 words • 100.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 4 words • 100.0% coverageWriter's voice • 25 words • 100.0% coverageWriter's voice • 21 words • 100.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageAlexandria Ocasio-Cortez • 18 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 28 words • 100.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 21 words • 100.0% coveragePaul Rivera • 23 words • 100.0% coverageWriter's voice • 25 words • 100.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 19 words • 100.0% coverageWriter's voice • 22 words • 100.0% coverageWriter's voice • 24 words • 100.0% coverageWriter's voice • 5 words • 0.0% coveragePaul Rivera • 32 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverage
Selected voice

Paul Rivera

100%flagged-word coverage
55 attributed words75% of attributed speech79% writer coverage
0%27.5%55.0%Biased Writer Voice-51.4 ptsWriter: 51.4%Paul Rivera: 0.0%0.0%Unattributed Quote+32.8 ptsWriter: 9.1%Paul Rivera: 41.8%41.8%Politically Left Leaning B-5.3 ptsWriter: 5.3%Paul Rivera: 0.0%0.0%Quote-first Misdirection-5.1 ptsWriter: 5.1%Paul Rivera: 0.0%0.0%Politically Right Leaning -4.6 ptsWriter: 4.6%Paul Rivera: 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.