BS Summary: This article contains 17 faulty reasoning types, including Ambiguity (Equivocation), Hasty Generalization, and Appeal to Emotion, with Negativity Bias as the most egregious example at 36.3% saturation with 316 hits. Analysis detected 1,184 faulty-reasoning hits from 871 analyzed words, generating a BS Score of 33% and a BS Rank of 28% (19,795 of 27,294 articles). This article is better (less manipulative) than 72.50% of the article peer group.

State lawmakers are returning to Sacramento today for the final month of session, which ends on Aug. 
31. 
In the next few weeks, Democratic legislative leaders will attempt to hammer out deals between themselves, Gov. 
Gavin Newsom and other stakeholders on bills related to climate policy, speeding up urban development, wildfires and more, write CalMatters’ Yue Stella Yu and Maya C. 
Miller. 
Major deals we’re keeping tabs on include : 
Climate funding: By the June state budget deadline, legislators and Newsom failed to agree on how to spend the state’s main climate fund. 
The parties last year reauthorized the state’s carbon market, which finances climate programs by charging companies that pollute. 
But that money, which was estimated to generate $4 billion a year, could shrink by half under new rules the Newsom administration adopted this year  putting money for various legislative priorities at risk. 
California Forever: The real estate development group, backed by tech billionaires, wants to turn large parts of Solano County farmland into a new Bay Area city. 
It is seeking a carveout on environmental rules to speed up this project, but no legislation materialized to help it do so. 
After a shipyard company chose Texas instead of California Forever’s site for its newest location, the group  which Newsom appears to support  is growing impatient with lawmakers. 
Utilities’ liability: Newsom’s latest proposal to address wildfire risks has consumer advocates, wildfire survivors and insurance companies accusing the governor of trying to reduce utilities’ liability for wildfires they cause. 
They all allege that the legislative proposal, which doesn’t have a lot of details because there is no bill language yet, would limit compensation for fire victims and eliminate insurers’ right to recover wildfire costs from utilities. 
Meanwhile, lawmakers have remained mum on the governor’s proposal. 
CalMatters events: Join us Wednesday in Riverside for a free conversation about how California will educate its future workforce. 
CalMatters’ Adam Echelman will moderate a discussion with health, education and workforce leaders. 
Register here . 
CalMatters and inewsource are also hosting a conversation on Aug. 13 in San Ysidro about the Tijuana River contamination crisis, an environmental emergency affecting millions on both sides of the U.S.-Mexico border. 
Register . 
Other Stories You Should Know 
The nonprofit that would gain billions in CA ballot measure 
Proposition 38 on the November ballot would provide $8.4 billion for immunology research that could help find cures for heart disease, cancer and Alzheimer’s. 
But upon closer analysis, the measure appears to be written in a way that enables only one institute in California to receive half the money , reports CalMatters’ Mikhail Zinshteyn. 
As written, the bond proposal would mete over $4 billion to select nonprofit and public university researchers who apply for competitive grants. 
But the other $4 million would be allocated to one unnamed institute that must meet very specific criteria, including being founded before 2025, meeting a minimum square footage requirement and being affiliated with a University of California campus with a medical center that serves a minimum number of patients that currently only UCLA meets. 
These criteria seem to leave only the California Institute for Immunology and Immunotherapy eligible for the bond money. 
The nonprofit institute was co-founded by billionaire Gary Michelson, who has donated more than $100 million to the institute and is also one of the top wealthy backers of Prop. 
38. 
Michelson and a nonprofit that he founded has donated at least $8.2 million to the Yes on Proposition 38 campaign, while Meyer Luskin, another institute co-founder, donated at least $5 million. 
Push to regulate license plate readers 
Proponents of a bill that would limit California law enforcement’s use of automated license plate readers say the proposal would protect people’s privacy from police overreach. 
But police agencies and officers’ unions argue that the bill would impede their ability to fight crime , writes CalMatters’ Ryan Sabalow. 
Thousands of cameras from at least 230 police and sheriffs’ departments are posted along roadways or installed on patrol cars. 
The bill would cap the time agencies can keep license plate data to 30 days, with some exceptions, and also limit who can access the data. 
The bill would also prohibit law enforcement departments from entering into contracts with camera companies that give federal and out-of-state police default access to plate databases. 
But in defense of the plate readers, police agencies say the technology has helped solve murders, recover stolen vehicles and investigate serious crimes including robberies, kidnappings, retail thefts and DUIs. 
And lastly: Special report coming Tuesday 
By some estimates California’s uninsured rate is expected to double in the next four years to 15% as a combination of federal and state healthcare cuts take hold. 
We’re launching a special project and documentary Tuesday to explore what that trend means both for people who will lose insurance and for Californians who may find less access to care even if they’re covered. 
California agencies are inconsistent when reporting bond expenditures and they often emphasize dollars spent rather than results achieved  leaving legislators, taxpayers and voters an unclear picture of what worked and what needs improvement, writes Cathy Cockrum Dean , president and founder of Elevate California. 
Article reasoning-pattern comparisonThis article: 2.1%Lynn La: 1.4%CalMatters: 2.2%Confirmation Bias2.1%This article: 0.0%Lynn La: 0.5%CalMatters: 0.7%Anchoring Bias0.0%This article: 6.7%Lynn La: 2.5%CalMatters: 2.3%Availability Heuristic6.7%This article: 0.0%Lynn La: 0.4%CalMatters: 0.8%Representativeness Heuristic0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.4%Hindsight Bias0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.7%Overconfidence Bias0.0%This article: 7.1%Lynn La: 5.6%CalMatters: 4.7%Framing Effect7.1%This article: 7.9%Lynn La: 0.9%CalMatters: 0.6%Loss Aversion7.9%This article: 0.0%Lynn La: 0.5%CalMatters: 0.5%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: 1.4%Optimism Bias0.0%This article: 3.2%Lynn La: 1.7%CalMatters: 1.7%Pessimism Bias3.2%This article: 36.3%Lynn La: 8.6%CalMatters: 7.0%Negativity Bias36.3%This article: 0.0%Lynn La: 1.3%CalMatters: 1.3%Self-Serving Bias0.0%This article: 0.0%Lynn La: 0.8%CalMatters: 0.7%Fundamental Attribution Error0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.2%Actor-Observer Bias0.0%This article: 0.0%Lynn La: 0.8%CalMatters: 0.5%In-Group Bias0.0%This article: 0.0%Lynn La: 0.3%CalMatters: 0.2%Out-Group Homogeneity Bias0.0%This article: 3.4%Lynn La: 0.6%CalMatters: 1.0%Halo Effect3.4%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: 0.5%CalMatters: 0.9%Recency Bias0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.1%Primacy Effect0.0%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Blind-Spot Bias0.0%This article: 0.0%Lynn La: 0.6%CalMatters: 0.4%Ad Hominem0.0%This article: 0.0%Lynn La: 0.1%CalMatters: 0.2%Straw Man0.0%This article: 3.4%Lynn La: 2.9%CalMatters: 2.7%Appeal to Authority3.4%This article: 0.0%Lynn La: 0.9%CalMatters: 0.8%False Dilemma0.0%This article: 3.2%Lynn La: 0.7%CalMatters: 1.0%Slippery Slope3.2%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Circular Reasoning0.0%This article: 11.4%Lynn La: 3.5%CalMatters: 2.9%Hasty Generalization11.4%This article: 0.0%Lynn La: 0.2%CalMatters: 0.2%Red Herring0.0%This article: 0.0%Lynn La: 0.4%CalMatters: 0.3%Bandwagon0.0%This article: 10.8%Lynn La: 5.5%CalMatters: 4.1%Appeal to Emotion10.8%This article: 0.0%Lynn La: 0.8%CalMatters: 0.6%Begging the Question0.0%This article: 6.5%Lynn La: 1.7%CalMatters: 2.1%Post Hoc (False Cause)6.5%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Tu Quoque0.0%This article: 0.0%Lynn La: 0.0%CalMatters: 0.3%Burden of Proof0.0%This article: 0.0%Lynn La: 0.1%CalMatters: 0.1%Appeal to Nature0.0%This article: 0.0%Lynn La: 0.1%CalMatters: 0.2%Composition/Division0.0%This article: 3.4%Lynn La: 2.1%CalMatters: 1.7%Anecdotal3.4%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%No True Scotsman0.0%This article: 11.5%Lynn La: 1.3%CalMatters: 1.0%Ambiguity (Equivocation)11.5%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Lynn La: 0.1%CalMatters: 0.1%Middle Ground0.0%This article: 0.0%Lynn La: 0.0%CalMatters: 0.0%Personal Incredulity0.0%This article: 0.0%Lynn La: 0.3%CalMatters: 0.2%Special Pleading0.0%This article: 7.0%Lynn La: 0.4%CalMatters: 0.1%Genetic Fallacy7.0%This article: 0.0%Lynn La: 1.5%CalMatters: 0.7%Unattributed Quote0.0%This article: 0.0%Lynn La: 1.2%CalMatters: 0.6%Quote-first Misdirection0.0%This article: 5.2%Lynn La: 3.6%CalMatters: 2.4%Biased Writer Voice5.2%This article: 0.0%Lynn La: 1.7%CalMatters: 0.8%Indoctrination0.0%This article: 0.0%Lynn La: 0.6%CalMatters: 0.5%Politically Left Leaning Bias0.0%This article: 0.0%Lynn La: 0.2%CalMatters: 0.1%Politically Right Leaning Bias0.0%This article: 6.8%Lynn La: 3.4%CalMatters: 0.8%Attempt to Sell a Product or S…6.8%

871 words analyzed.

Speakers

4speakers18%attributed speech710writer words
Selected voice

Cathy Cockrum Dean

100%flagged-word coverage
45 attributed words28% of attributed speech66% writer coverage
0%50.0%100.0%Biased Writer Voice+100.0 ptsWriter: 0.0%Cathy Cockrum Dean: 100.0%100.0%Attempt to Sell a Product -5.6 ptsWriter: 5.6%Cathy Cockrum Dean: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

Loading…
Loading…
Loading…
Loading…

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.