BS Summary: This article contains 11 faulty reasoning types, including Appeal to Authority, Quote-first Misdirection, and Framing Effect, with Overconfidence Bias as the most egregious example at 27.6% saturation with 50 hits. Analysis detected 352 faulty-reasoning hits from 181 analyzed words, generating a BS Score of 35.9% and a BS Rank of 33% (17,925 of 26,543 articles). This article is better (less manipulative) than 67.50% of the article peer group.

Forget the birds and other environmental impacts, are taller buildings messing with lunar cycles? 
On this week’s show, our hosts explain how a proposed bill would stop building height from being treated as a significant environmental impact under state law. 
State Sen. 
Akilah Weber Pierson spoke about SB 958 at a committee hearing in June and explained how environmental laws have sometimes been used to slow housing projects. 
She cited Midway Rising and litigation that has stood in the project’s way. 
“Despite years of analysis and multiple EIRs, the most recent ruling from the California’s fourth district court of appeal determined that environmental review when related to building height needed to include aspects that were not typically analyzed, including impacts on airflow, atmospheric conditions, lunar cycles, and wildlife attraction,” she said. 
Lunar cycles? 
Co-host Scott Lewis explains what’s at stake and why we’re going to keep talking about SB 958. 
Also on the show: The state is moving forward with a mesh barrier to deter suicides on the Coronado Bridge. 
They also plan to install AI cameras. 
Article reasoning-pattern comparisonThis article: 21.5%Matt Skraby: 2.2%Voice of San Diego: 2.2%Confirmation Bias21.5%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.5%Anchoring Bias0.0%This article: 0.0%Matt Skraby: 7.3%Voice of San Diego: 2.0%Availability Heuristic0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.6%Representativeness Heuristic0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.4%Hindsight Bias0.0%This article: 27.6%Matt Skraby: 2.8%Voice of San Diego: 0.7%Overconfidence Bias27.6%This article: 22.1%Matt Skraby: 9.2%Voice of San Diego: 4.5%Framing Effect22.1%This article: 11.0%Matt Skraby: 1.1%Voice of San Diego: 0.4%Loss Aversion11.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.5%Status Quo Bias0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.2%Sunk Cost Effect0.0%This article: 0.0%Matt Skraby: 0.7%Voice of San Diego: 2.2%Optimism Bias0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 1.0%Pessimism Bias0.0%This article: 7.7%Matt Skraby: 2.3%Voice of San Diego: 6.7%Negativity Bias7.7%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 1.3%Self-Serving Bias0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.7%Fundamental Attribution Error0.0%This article: 14.4%Matt Skraby: 1.5%Voice of San Diego: 0.1%Actor-Observer Bias14.4%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.6%In-Group Bias0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.2%Out-Group Homogeneity Bias0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 1.2%Halo Effect0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.0%Horn Effect0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.0%Dunning-Kruger Effect0.0%This article: 9.4%Matt Skraby: 1.0%Voice of San Diego: 0.8%Recency Bias9.4%This article: 0.0%Matt Skraby: 1.1%Voice of San Diego: 0.3%Primacy Effect0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.0%Blind-Spot Bias0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.5%Ad Hominem0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.2%Straw Man0.0%This article: 27.6%Matt Skraby: 5.6%Voice of San Diego: 2.1%Appeal to Authority27.6%This article: 0.0%Matt Skraby: 0.9%Voice of San Diego: 0.9%False Dilemma0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.5%Slippery Slope0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.1%Circular Reasoning0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 3.1%Hasty Generalization0.0%This article: 0.0%Matt Skraby: 1.6%Voice of San Diego: 0.1%Red Herring0.0%This article: 0.0%Matt Skraby: 1.0%Voice of San Diego: 0.4%Bandwagon0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 3.1%Appeal to Emotion0.0%This article: 0.0%Matt Skraby: 0.2%Voice of San Diego: 0.4%Begging the Question0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 1.6%Post Hoc (False Cause)0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.1%Tu Quoque0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.4%Burden of Proof0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.0%Appeal to Nature0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.1%Composition/Division0.0%This article: 21.5%Matt Skraby: 6.1%Voice of San Diego: 1.6%Anecdotal21.5%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.1%No True Scotsman0.0%This article: 0.0%Matt Skraby: 2.4%Voice of San Diego: 1.0%Ambiguity (Equivocation)0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.1%Middle Ground0.0%This article: 0.0%Matt Skraby: 0.1%Voice of San Diego: 0.0%Personal Incredulity0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.1%Special Pleading0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.3%Genetic Fallacy0.0%This article: 0.0%Matt Skraby: 2.9%Voice of San Diego: 1.2%Unattributed Quote0.0%This article: 27.6%Matt Skraby: 8.6%Voice of San Diego: 0.6%Quote-first Misdirection27.6%This article: 0.0%Matt Skraby: 4.4%Voice of San Diego: 5.2%Biased Writer Voice0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.9%Indoctrination0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.6%Politically Left Leaning Bias0.0%This article: 0.0%Matt Skraby: 0.0%Voice of San Diego: 0.1%Politically Right Leaning Bias0.0%This article: 3.9%Matt Skraby: 1.7%Voice of San Diego: 1.1%Attempt to Sell a Product or S…3.9%

181 words analyzed.

Speakers

2speakers59%attributed speech75writer words
Selected voice

Akilah Weber Pierson

100%flagged-word coverage
89 attributed words84% of attributed speech89% writer coverage
0%30.0%60.0%Quote-first Misdirection+56.2 ptsWriter: 0.0%Akilah Weber Pierson: 56.2%56.2%Attempt to Sell a Product -9.3 ptsWriter: 9.3%Akilah Weber Pierson: 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.