KQED⁠61%

LA Mayor’s Race May Become a ‘Slugfest’ Between Former Allies ⁠71%

By Lesley McClurg⁠0% Guy Marzorati⁠71%

6/18/2026, 4:11:36 PM

BS Summary: This article contains 13 faulty reasoning types, including Appeal to Authority, Representativeness Heuristic, and Hasty Generalization, with Framing Effect as the most egregious example at 35.1% saturation with 59 hits. Analysis detected 391 faulty-reasoning hits from 168 analyzed words, generating a BS Score of 63.8% and a BS Rank of ⁠71% (6,367 of 21,887 articles). This article is worse (more manipulative) than 70.90% of the article peer group.

The feud between Gov. 
Gavin Newsom and President Donald Trump escalated this week, with Newsom announcing the U.S. 
Department of Justice is investigating him and his wife. 
The decision to announce publicly before any official charges is unusual, but the investigation may help elevate Newsom as he weighs a possible presidential run. 
KQED’s Lesley McClurg and Guy Marzorati discuss what we know so far about the investigation and how it fits into Trump’s broader weaponization of the DOJ. 
Plus: the race for Los Angeles mayor is headed to a runoff between two Democrats, and some expect it to be a “slugfest.” 
The candidates, Mayor Karen Bass and City Councilmember Nithya Raman, share many of the same policy goals, so the battle may be less about ideology and more about Bass’ record and Raman’s call for change. 
Lesley is joined by Mike Bonin, a former Los Angeles City Councilmember who now leads the Pat Brown Institute for Public Affairs. 
Article reasoning-pattern comparisonThis article: 15.5%Lesley McClurg: 6.3%CalMatters: 1.9%Confirmation Bias15.5%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.9%Anchoring Bias0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 3.0%Availability Heuristic0.0%This article: 20.8%Lesley McClurg: 3.2%CalMatters: 1.0%Representativeness Heuristic20.8%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.5%Hindsight Bias0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 1.2%Overconfidence Bias0.0%This article: 35.1%Lesley McClurg: 25.6%CalMatters: 6.3%Framing Effect35.1%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 1.0%Loss Aversion0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.7%Status Quo Bias0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.2%Sunk Cost Effect0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 3.5%Optimism Bias0.0%This article: 14.9%Lesley McClurg: 3.9%CalMatters: 1.4%Pessimism Bias14.9%This article: 0.0%Lesley McClurg: 10.3%CalMatters: 6.4%Negativity Bias0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 1.7%Self-Serving Bias0.0%This article: 0.0%Lesley McClurg: 7.4%CalMatters: 0.7%Fundamental Attribution Error0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.2%Actor-Observer Bias0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 1.7%In-Group Bias0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.4%Out-Group Homogeneity Bias0.0%This article: 13.1%Lesley McClurg: 2.0%CalMatters: 2.7%Halo Effect13.1%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.1%Horn Effect0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.0%Dunning-Kruger Effect0.0%This article: 8.3%Lesley McClurg: 1.3%CalMatters: 0.9%Recency Bias8.3%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.3%Primacy Effect0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.0%Blind-Spot Bias0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.6%Ad Hominem0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.2%Straw Man0.0%This article: 28.6%Lesley McClurg: 4.4%CalMatters: 3.1%Appeal to Authority28.6%This article: 0.0%Lesley McClurg: 6.4%CalMatters: 1.1%False Dilemma0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.8%Slippery Slope0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.1%Circular Reasoning0.0%This article: 20.8%Lesley McClurg: 12.3%CalMatters: 3.6%Hasty Generalization20.8%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.2%Red Herring0.0%This article: 13.7%Lesley McClurg: 2.1%CalMatters: 0.7%Bandwagon13.7%This article: 0.0%Lesley McClurg: 2.4%CalMatters: 5.3%Appeal to Emotion0.0%This article: 15.5%Lesley McClurg: 4.8%CalMatters: 0.6%Begging the Question15.5%This article: 14.9%Lesley McClurg: 6.2%CalMatters: 2.0%Post Hoc (False Cause)14.9%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.1%Tu Quoque0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.3%Burden of Proof0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.2%Appeal to Nature0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.2%Composition/Division0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 3.1%Anecdotal0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.0%No True Scotsman0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 1.2%Ambiguity (Equivocation)0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.1%Middle Ground0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.1%Personal Incredulity0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.1%Special Pleading0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.1%Genetic Fallacy0.0%This article: 13.7%Lesley McClurg: 2.1%CalMatters: 0.8%Unattributed Quote13.7%This article: 0.0%Lesley McClurg: 2.1%CalMatters: 0.7%Quote-first Misdirection0.0%This article: 17.9%Lesley McClurg: 8.6%CalMatters: 3.1%Biased Writer Voice17.9%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 1.9%Indoctrination0.0%This article: 0.0%Lesley McClurg: 4.8%CalMatters: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Lesley McClurg: 0.0%CalMatters: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Lesley McClurg: 4.0%CalMatters: 1.2%Attempt to Sell a Product or S…0.0%

168 words analyzed.

Speakers

1speaker15%attributed speech142writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 10 words • 0.0% coverageWriter's voice • 4 words • 100.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageKQED’s Lesley McClurg and Guy Marzorati • 26 words • 100.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 35 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverage
100%flagged-word coverage
26 attributed words100% of attributed speech94% writer coverage
0%50.0%100.0%Biased Writer Voice+97.2 ptsWriter: 2.8%KQED’s Lesley McClurg and Guy Marzorati: 100.0%100.0%Unattributed Quote-16.2 ptsWriter: 16.2%KQED’s Lesley McClurg and Guy Marzorati: 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.