KQED⁠60%

Daniel Lurie’s Endorsements Are Dominating San Francisco’s Early Returns ⁠56%

By Scott Shafer⁠0% Marisa Lagos⁠88% Guy Marzorati⁠70% Sydney Johnson⁠57%

6/5/2026, 11:05:46 PM

BS Summary: This article contains 13 faulty reasoning types, including Biased Writer Voice, Confirmation Bias, and Recency Bias, with Hasty Generalization as the most egregious example at 79.3% saturation with 73 hits. Analysis detected 350 faulty-reasoning hits from 92 analyzed words, generating a BS Score of 54.1% and a BS Rank of ⁠56% (8,958 of 20,368 articles). This article is worse (more manipulative) than 56.00% of the article peer group.

With primary week drawing to a close, San Francisco’s early returns suggest that two people not on the ballot have come out on top: Mayor Daniel Lurie and Rep. 
Nancy Pelosi. 
Scott, Marisa, Guy and KQED’s Sydney Johnson turn to the races and ballot measures in San Francisco, analyzing what the results so far tell us, even with nearly half the votes still left to count. 
Track the latest election results here. 
Check out Political Breakdown’s weekly newsletter, delivered straight to your inbox. 
Article reasoning-pattern comparisonThis article: 38.0%Scott Shafer: 6.3%CalMatters: 1.9%Confirmation Bias38.0%This article: 31.5%Scott Shafer: 2.7%CalMatters: 0.9%Anchoring Bias31.5%This article: 0.0%Scott Shafer: 6.5%CalMatters: 3.0%Availability Heuristic0.0%This article: 0.0%Scott Shafer: 1.3%CalMatters: 1.0%Representativeness Heuristic0.0%This article: 0.0%Scott Shafer: 2.0%CalMatters: 0.5%Hindsight Bias0.0%This article: 0.0%Scott Shafer: 1.3%CalMatters: 1.2%Overconfidence Bias0.0%This article: 9.8%Scott Shafer: 30.0%CalMatters: 6.3%Framing Effect9.8%This article: 0.0%Scott Shafer: 0.2%CalMatters: 1.0%Loss Aversion0.0%This article: 0.0%Scott Shafer: 2.2%CalMatters: 0.7%Status Quo Bias0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.2%Sunk Cost Effect0.0%This article: 31.5%Scott Shafer: 3.5%CalMatters: 3.6%Optimism Bias31.5%This article: 0.0%Scott Shafer: 0.9%CalMatters: 1.4%Pessimism Bias0.0%This article: 9.8%Scott Shafer: 22.1%CalMatters: 6.4%Negativity Bias9.8%This article: 0.0%Scott Shafer: 1.9%CalMatters: 1.7%Self-Serving Bias0.0%This article: 0.0%Scott Shafer: 1.3%CalMatters: 0.7%Fundamental Attribution Error0.0%This article: 0.0%Scott Shafer: 0.3%CalMatters: 0.2%Actor-Observer Bias0.0%This article: 0.0%Scott Shafer: 3.8%CalMatters: 1.7%In-Group Bias0.0%This article: 0.0%Scott Shafer: 2.1%CalMatters: 0.4%Out-Group Homogeneity Bias0.0%This article: 0.0%Scott Shafer: 5.3%CalMatters: 2.7%Halo Effect0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.1%Horn Effect0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.0%Dunning-Kruger Effect0.0%This article: 38.0%Scott Shafer: 7.0%CalMatters: 0.9%Recency Bias38.0%This article: 9.8%Scott Shafer: 1.5%CalMatters: 0.3%Primacy Effect9.8%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.0%Blind-Spot Bias0.0%This article: 0.0%Scott Shafer: 1.3%CalMatters: 0.6%Ad Hominem0.0%This article: 0.0%Scott Shafer: 0.2%CalMatters: 0.2%Straw Man0.0%This article: 0.0%Scott Shafer: 7.6%CalMatters: 3.1%Appeal to Authority0.0%This article: 31.5%Scott Shafer: 2.4%CalMatters: 1.1%False Dilemma31.5%This article: 0.0%Scott Shafer: 0.3%CalMatters: 0.8%Slippery Slope0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.1%Circular Reasoning0.0%This article: 79.3%Scott Shafer: 4.2%CalMatters: 3.6%Hasty Generalization79.3%This article: 0.0%Scott Shafer: 2.5%CalMatters: 0.2%Red Herring0.0%This article: 0.0%Scott Shafer: 2.7%CalMatters: 0.7%Bandwagon0.0%This article: 0.0%Scott Shafer: 7.5%CalMatters: 5.3%Appeal to Emotion0.0%This article: 31.5%Scott Shafer: 2.7%CalMatters: 0.6%Begging the Question31.5%This article: 0.0%Scott Shafer: 3.9%CalMatters: 2.0%Post Hoc (False Cause)0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.1%Tu Quoque0.0%This article: 0.0%Scott Shafer: 0.2%CalMatters: 0.3%Burden of Proof0.0%This article: 0.0%Scott Shafer: 0.2%CalMatters: 0.2%Appeal to Nature0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.2%Composition/Division0.0%This article: 0.0%Scott Shafer: 1.7%CalMatters: 3.1%Anecdotal0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.0%No True Scotsman0.0%This article: 9.8%Scott Shafer: 1.3%CalMatters: 1.2%Ambiguity (Equivocation)9.8%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.1%Middle Ground0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.1%Personal Incredulity0.0%This article: 0.0%Scott Shafer: 0.0%CalMatters: 0.1%Special Pleading0.0%This article: 0.0%Scott Shafer: 1.6%CalMatters: 0.2%Genetic Fallacy0.0%This article: 0.0%Scott Shafer: 1.8%CalMatters: 0.8%Unattributed Quote0.0%This article: 0.0%Scott Shafer: 2.0%CalMatters: 0.6%Quote-first Misdirection0.0%This article: 41.3%Scott Shafer: 20.5%CalMatters: 3.1%Biased Writer Voice41.3%This article: 0.0%Scott Shafer: 0.7%CalMatters: 1.9%Indoctrination0.0%This article: 0.0%Scott Shafer: 8.4%CalMatters: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Scott Shafer: 1.0%CalMatters: 0.1%Politically Right Leaning Bias0.0%This article: 18.5%Scott Shafer: 8.5%CalMatters: 1.2%Attempt to Sell a Product or S…18.5%

92 words analyzed.

Speakers

2speakers14%attributed speech79writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 100.0% coverageWriter's voice • 29 words • 100.0% coverageNancy Pelosi • 2 words • 0.0% coverageWriter's voice • 35 words • 0.0% coverageWriter's voice • 6 words • 100.0% coveragePolitical Breakdown • 11 words • 100.0% coverage
Selected voice

Political Breakdown

100%flagged-word coverage
11 attributed words85% of attributed speech100% writer coverage
0%50.0%100.0%Attempt to Sell a Product +92.4 ptsWriter: 7.6%Political Breakdown: 100.0%100.0%Biased Writer Voice-48.1 ptsWriter: 48.1%Political Breakdown: 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.