UCSF chancellor flubs biology –– but aces Evasion 101 ⁠97%

By CA Post Editorial Board⁠99%

7/16/2026, 12:36:37 AM

BS Summary: This article contains 29 faulty reasoning types, including Negativity Bias, Politically Right Leaning Bias, and Ad Hominem, with Biased Writer Voice as the most egregious example at 87.3% saturation with 338 hits. Analysis detected 1,867 faulty-reasoning hits from 387 analyzed words, generating a BS Score of 94.3% and a BS Rank of ⁠97% (799 of 21,887 articles). This article is worse (more manipulative) than 96.40% of the article peer group.

The head of a prestigious health sciences university, of all people, should understand simple biology. 
Yet Dr. 
Sam Hawgood, a pediatrician and the chancellor of UC San Francisco, this week struggled to concede that only women can bear children. 
Under questioning from Illinois Rep. 
Mary Miller at a House committee hearing on DEI in medicine, the good doctor prevaricated. 
Miller: “Has a nonbiological woman ever had a baby?” 
Hawgood: “A transgender person can.” 
Miller: That’s not a nonbiological woman (and she repeated the question). 
Oh dear. 
Let’s be real here: The advice to say “pregnant people” and not “pregnant women” –– which appears in UCSF’s “Framework for Gender and Sex Concepts in Teaching” –– is not just wrong. 
It’s an insult to women everywhere to use words that would erase the reproductive capacity that makes them distinct, instead claiming that any man, anytime, can be a woman –– and be *the same*, like magic! 
No biological man/nonbiological woman has ever given birth, because it’s physically impossible. 
The fact that Hawgood –– an accomplished physician and administrator with reported annual compensation of $1 million –– could not admit that, in clear terms, does not reflect well on him, his institution, or the state of medical-school training generally. 
Instead, it suggests that Hawgood and others like him are more interested in genuflecting to far-left ideology than they are in basic medical reality. 
And they’re training the next generation of doctors? 
At best, medical students lose valuable instructional time to lectures on politics dressed up as inclusion. 
At worst, Californians get less competent doctors who may care more about gender theory than healing patients. 
Another side effect of putting ideology above truth: the erosion of trust in authority. 
Who can forget Justice Ketanji Brown Jackson’s inability to define “woman” during her 2022 Supreme Court confirmation hearings? 
Her credibility has never fully recovered. 
The same fate awaits Hawgood and Dr. 
Steve Dubinett, dean of UCLA’s David Geffen School of Medicine. 
Dubinett likewise stumbled through the House committee hearing on DEI –– stumped, apparently, by the question of whether someone can have a uterus but not be a woman. 
What a spectacle. 
Before the House and the world, these esteemed doctors aced Evasion 101 but flubbed tests of truth, leadership and basic science. 
Article reasoning-pattern comparisonThis article: 19.6%CA Post Editorial Board: 13.5%California Post: 4.1%Confirmation Bias19.6%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 1.4%Anchoring Bias0.0%This article: 5.9%CA Post Editorial Board: 3.9%California Post: 4.2%Availability Heuristic5.9%This article: 0.0%CA Post Editorial Board: 0.3%California Post: 1.1%Representativeness Heuristic0.0%This article: 0.0%CA Post Editorial Board: 3.4%California Post: 0.8%Hindsight Bias0.0%This article: 0.0%CA Post Editorial Board: 0.6%California Post: 2.2%Overconfidence Bias0.0%This article: 17.6%CA Post Editorial Board: 11.7%California Post: 10.3%Framing Effect17.6%This article: 9.3%CA Post Editorial Board: 1.5%California Post: 0.9%Loss Aversion9.3%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 0.6%Status Quo Bias0.0%This article: 0.0%CA Post Editorial Board: 0.4%California Post: 0.2%Sunk Cost Effect0.0%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 2.5%Optimism Bias0.0%This article: 17.8%CA Post Editorial Board: 1.7%California Post: 1.5%Pessimism Bias17.8%This article: 43.7%CA Post Editorial Board: 28.0%California Post: 16.0%Negativity Bias43.7%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 2.4%Self-Serving Bias0.0%This article: 12.9%CA Post Editorial Board: 3.0%California Post: 1.5%Fundamental Attribution Error12.9%This article: 10.3%CA Post Editorial Board: 1.0%California Post: 0.2%Actor-Observer Bias10.3%This article: 0.0%CA Post Editorial Board: 1.3%California Post: 1.6%In-Group Bias0.0%This article: 6.2%CA Post Editorial Board: 2.5%California Post: 1.1%Out-Group Homogeneity Bias6.2%This article: 15.8%CA Post Editorial Board: 3.1%California Post: 3.1%Halo Effect15.8%This article: 0.0%CA Post Editorial Board: 3.8%California Post: 0.6%Horn Effect0.0%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 0.0%Dunning-Kruger Effect0.0%This article: 4.7%CA Post Editorial Board: 2.0%California Post: 1.6%Recency Bias4.7%This article: 0.0%CA Post Editorial Board: 0.2%California Post: 0.5%Primacy Effect0.0%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 0.0%Blind-Spot Bias0.0%This article: 27.4%CA Post Editorial Board: 16.6%California Post: 2.6%Ad Hominem27.4%This article: 21.2%CA Post Editorial Board: 8.0%California Post: 0.5%Straw Man21.2%This article: 22.5%CA Post Editorial Board: 3.6%California Post: 4.2%Appeal to Authority22.5%This article: 17.6%CA Post Editorial Board: 3.3%California Post: 1.5%False Dilemma17.6%This article: 9.6%CA Post Editorial Board: 3.0%California Post: 0.9%Slippery Slope9.6%This article: 0.0%CA Post Editorial Board: 0.3%California Post: 0.2%Circular Reasoning0.0%This article: 6.5%CA Post Editorial Board: 12.9%California Post: 5.5%Hasty Generalization6.5%This article: 0.0%CA Post Editorial Board: 2.1%California Post: 0.7%Red Herring0.0%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 1.4%Bandwagon0.0%This article: 18.9%CA Post Editorial Board: 16.6%California Post: 8.9%Appeal to Emotion18.9%This article: 3.1%CA Post Editorial Board: 3.1%California Post: 1.1%Begging the Question3.1%This article: 14.0%CA Post Editorial Board: 9.4%California Post: 2.7%Post Hoc (False Cause)14.0%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 0.2%Tu Quoque0.0%This article: 3.9%CA Post Editorial Board: 0.9%California Post: 0.8%Burden of Proof3.9%This article: 0.0%CA Post Editorial Board: 1.7%California Post: 0.2%Appeal to Nature0.0%This article: 10.3%CA Post Editorial Board: 1.0%California Post: 0.2%Composition/Division10.3%This article: 4.7%CA Post Editorial Board: 1.3%California Post: 3.6%Anecdotal4.7%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 0.0%No True Scotsman0.0%This article: 16.8%CA Post Editorial Board: 3.1%California Post: 2.0%Ambiguity (Equivocation)16.8%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 0.0%Gambler’s Fallacy0.0%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 0.1%Middle Ground0.0%This article: 0.0%CA Post Editorial Board: 0.3%California Post: 0.1%Personal Incredulity0.0%This article: 0.0%CA Post Editorial Board: 0.0%California Post: 0.2%Special Pleading0.0%This article: 0.0%CA Post Editorial Board: 1.8%California Post: 0.4%Genetic Fallacy0.0%This article: 2.3%CA Post Editorial Board: 1.3%California Post: 3.2%Unattributed Quote2.3%This article: 8.8%CA Post Editorial Board: 0.8%California Post: 2.1%Quote-first Misdirection8.8%This article: 87.3%CA Post Editorial Board: 49.2%California Post: 13.1%Biased Writer Voice87.3%This article: 6.2%CA Post Editorial Board: 3.0%California Post: 1.4%Indoctrination6.2%This article: 0.0%CA Post Editorial Board: 0.6%California Post: 0.4%Politically Left Leaning Bias0.0%This article: 37.7%CA Post Editorial Board: 28.3%California Post: 3.0%Politically Right Leaning Bias37.7%This article: 0.0%CA Post Editorial Board: 3.6%California Post: 6.0%Attempt to Sell a Product or S…0.0%

387 words analyzed.

Speakers

3speakers26%attributed speech287writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 100.0% coverageWriter's voice • 15 words • 100.0% coverageWriter's voice • 2 words • 100.0% coverageSam Hawgood • 22 words • 100.0% coverageWriter's voice • 5 words • 0.0% coverageMary Miller • 15 words • 100.0% coverageMary Miller • 9 words • 100.0% coverageSam Hawgood • 5 words • 0.0% coverageMary Miller • 11 words • 0.0% coverageWriter's voice • 2 words • 100.0% coverageWriter's voice • 32 words • 100.0% coverageWriter's voice • 36 words • 100.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 40 words • 100.0% coverageWriter's voice • 24 words • 100.0% coverageWriter's voice • 8 words • 100.0% coverageWriter's voice • 16 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 18 words • 100.0% coverageWriter's voice • 6 words • 100.0% coverageWriter's voice • 7 words • 0.0% coverageSteve Dubinett • 10 words • 0.0% coverageSteve Dubinett • 28 words • 100.0% coverageWriter's voice • 3 words • 100.0% coverageWriter's voice • 21 words • 100.0% coverage
Selected voice

Sam Hawgood

100%flagged-word coverage
27 attributed words27% of attributed speech98% writer coverage
0%50.0%100.0%Biased Writer Voice-13.6 ptsWriter: 95.1%Sam Hawgood: 81.5%81.5%Politically Right Leaning -50.9 ptsWriter: 50.9%Sam Hawgood: 0.0%0.0%Quote-first Misdirection-11.8 ptsWriter: 11.8%Sam Hawgood: 0.0%0.0%Indoctrination-8.4 ptsWriter: 8.4%Sam Hawgood: 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.