San Francisco supervisors pass sweeping changes to city code 33%

By Kelly Waldron41%

7/14/2026, 11:37:02 PM

BS Summary: This article contains 23 faulty reasoning types, including Recency Bias, Appeal to Authority, and Primacy Effect, with Negativity Bias as the most egregious example at 16% saturation with 78 hits. Analysis detected 775 faulty-reasoning hits from 489 analyzed words, generating a BS Score of 41.7% and a BS Rank of 33% (10,572 of 15,741 articles). This article is better (less manipulative) than 67.20% of the article peer group.

The San Francisco Board of Supervisors voted 7-4 Tuesday to pass an ordinance that makes sweeping changes to the city’s municipal codes, despite objections that the 362-page ordinance is too broad to be covered by a single vote and concerns over changing some important reporting requirements including those around surveillance. 
The ordinance, sponsored by Board President Rafael Mandelman, originated at the city attorney’s office, whose staff partnered with a lab at Stanford University to use AI to identify redundancies in the city’s codes. 
Supervisors Myrna Melgar, Connie Chan, Jackie Fielder and Shamann Walton voted against the legislation. 
A previous vote, on June 30, was postponed by Mandelman for two weeks after several supervisors  and Angela Calvillo, the board clerk, who seldom weighs in on legislative discussion  raised concerns that the proposal was so broad, they could not make sense of all the changes being made. 
Calvillo described the ordinance as a “deviation from the norm” and Supervisor Melgar said she relied on AI  Anthropic’s Claude  to understand the specific changes in the ordinance. 
Many of the proposals reduce or remove requirements that mandate reports about certain aspects of city government. 
Supervisor Fielder raised concerns about how the ordinance changed the frequency of the city’s audit of its use of surveillance technology from every year to every five years. 
“I think the frequency of this report is crucial to honoring civil liberties and the intent of our city's strong surveillance technology policy,” said Fielder. 
Supervisor Walton echoed Fielder’s comments. 
“These reporting requirements are in place for a reason,” said Walton, who added that the ordinance should have been broken down into smaller pieces of legislation. 
Melgar agreed with the substance of the changes, she told the board, but took issue with the process of combining so many of them together. 
“There are policy implications for streamlining and getting rid of reports  that I think are policy decisions,” said Melgar. 
“I don’t think that the process was sufficient to encompass the entire breadth of what’s happening here,” Melgar added. 
Before the meeting, Melgar said she would look into introducing trailing legislation, which allows supervisors to follow-up with changes to existing legislation, at a later stage, to address concerns that weren’t addressed before the vote. 
Amendments made in the last two weeks include restoring reporting requirements that provide information to the Department of the Status on Women (among those requirements: the police department and district attorney’s office have to share domestic violence data). 
The recent amendments also restore reporting requirements on sexual harassment, and for reports on the number of small businesses served by case managers at the city’s Office of Small Business. 
At the meeting, Mandelman suggested that work remains to be done to streamline the city’s codes. 
“I hope this is not the end,” he said. 
“Because I do think our code needs much more pruning.” 
Confirmation Bias
2%
Anchoring Bias
0%
Availability Heuristic
3.5%
Representativeness Heuristic
6.1%
Hindsight Bias
0%
Overconfidence Bias
3.9%
Framing Effect
1.8%
Loss Aversion
0%
Status Quo Bias
5.3%
Sunk Cost Effect
0%
Optimism Bias
9%
Pessimism Bias
5.3%
Negativity Bias
16%
Self-Serving Bias
0%
Fundamental Attribution Error
0%
Actor-Observer Bias
5.1%
In-Group Bias
0%
Out-Group Homogeneity Bias
0%
Halo Effect
0%
Horn Effect
0%
Dunning-Kruger Effect
0%
Recency Bias
13.9%
Primacy Effect
10.2%
Blind-Spot Bias
0%
Ad Hominem
0%
Straw Man
0%
Appeal to Authority
12.9%
False Dilemma
10.2%
Slippery Slope
0%
Circular Reasoning
0%
Hasty Generalization
10.2%
Red Herring
0%
Bandwagon
1%
Appeal to Emotion
5.1%
Begging the Question
5.1%
Post Hoc (False Cause)
0%
Tu Quoque
0%
Burden of Proof
3.9%
Appeal to Nature
0%
Composition/Division
0%
Anecdotal
2%
No True Scotsman
0%
Ambiguity (Equivocation)
10.2%
Gambler’s Fallacy
0%
Middle Ground
5.3%
Personal Incredulity
0%
Special Pleading
0%
Genetic Fallacy
0%
Unattributed Quote
0%
Quote-first Misdirection
0%
Biased Writer Voice
10.2%
Indoctrination
0%
Politically Left Leaning Bias
0%
Politically Right Leaning Bias
0%
Attempt to Sell a Product or Service
0%

489 words analyzed.

Analysis

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