This Planet Fitness Member’s Account Shows Two Different Genders on Two Different Platforms  and the Internet Exploded 48%

By Vanshika54%

8/2/2026, 12:55:47 PM

BS Summary: This article contains 25 faulty reasoning types, including Negativity Bias, Burden of Proof, and False Dilemma, with Unattributed Quote as the most egregious example at 39% saturation with 196 hits. Analysis detected 1,004 faulty-reasoning hits from 503 analyzed words, generating a BS Score of 41.5% and a BS Rank of 48% (15,948 of 30,584 articles). This article is better (less manipulative) than 52.10% of the article peer group.

A Planet Fitness member has sparked debate online. 
They claimed the gym changed the gender listed on part of her account without notifying them. 
The video gained widespread attention after an X aggregator accounts reshared it. 
Commenters split over whether the issue reflected a technical error, a policy change, or something else. 
Planet Fitness just changed a woman’s gender on her account without telling her. 
She’s a biological female who years ago registered as “non-binary.” 
App still shows the delusion. 
Website? 
They quietly flipped her to male. 
She’s still using the women’s locker room for her own… pic.twitter.com/SxPP2KeXRx 
- DocumentingLibs (@HistorianUSA1) July 31, 2026 
In the video, the creator records themselves while demonstrating what they describe as a discrepancy between Planet Fitness’ mobile app and its website. 
They say they originally selected “Non-Binary” when creating her account but later noticed the website listed her gender as “Male.” 
They also revealed the mobile app still displays “Non-Binary.” 
The clip circulated widely after X account @HistorianUSA1 reposted it and had gained 26,000 views and 336 likes, at the time of publication. 
The Daily Dot could not locate the video’s original upload before it spread across X. 
The video itself does not explain why the two platforms display different information. 
Planet Fitness has not publicly addressed the clip or confirmed whether the discrepancy resulted from a software bug, an account update, or another technical issue. 
The video quickly spread across X, where users debated what the apparent mismatch could mean. 
Some commenters suggested the issue reflected inconsistent account syncing between the website and mobile app. 
Others questioned whether Planet Fitness intentionally changed account information. 
Those claims remain unverified. 
A commenter questioned, “If you were born a woman, why would they put you as a male? 
What is your drivers license say?” 
“So why isn’t she using the nonbinary locker room?” 
another asked. 
The discussion also broadened into conversations about gender identity policies at gyms, with many commenters focusing on locker room access, account settings, and company policy rather than the original technical discrepancy. 
A commenter wrote, “By her thinking nonbinary means not a man or a woman. 
So by that logic she doesn’t belong in either or since she is ‘neither’ then either should be ok. 
But no she wants to go in the women’s room because she knows she’s a woman.” 
Another wrote, “Really is the height of privilege to have no problems in life except your fictional “gender” games.” 
A third user wrote, “I was days away from joining Planet Fitness when I found out they allow biological MEN in women’s locker rooms! 
I walked away! 
Ladies…. 
JUST SAY NO!!!!!!” 
The repost also attracted numerous comments attacking transgender and non-binary people, including personal insults and slurs that The Daily Dot is not reproducing here. 
The Daily Dot could not independently verify the creator’s claims or determine what caused the different gender labels shown in the video. 
Article reasoning-pattern comparisonThis article: 7.8%Vanshika: 2.1%dailydot.com: 3.6%Confirmation Bias7.8%This article: 0.0%Vanshika: 0.8%dailydot.com: 0.8%Anchoring Bias0.0%This article: 11.5%Vanshika: 3.7%dailydot.com: 3.4%Availability Heuristic11.5%This article: 0.0%Vanshika: 0.4%dailydot.com: 1.0%Representativeness Heuristic0.0%This article: 0.0%Vanshika: 0.3%dailydot.com: 0.6%Hindsight Bias0.0%This article: 5.0%Vanshika: 1.0%dailydot.com: 1.3%Overconfidence Bias5.0%This article: 6.8%Vanshika: 3.7%dailydot.com: 4.0%Framing Effect6.8%This article: 0.0%Vanshika: 0.4%dailydot.com: 0.5%Loss Aversion0.0%This article: 0.0%Vanshika: 0.3%dailydot.com: 0.5%Status Quo Bias0.0%This article: 0.0%Vanshika: 0.1%dailydot.com: 0.2%Sunk Cost Effect0.0%This article: 0.0%Vanshika: 1.0%dailydot.com: 1.0%Optimism Bias0.0%This article: 0.6%Vanshika: 1.0%dailydot.com: 1.2%Pessimism Bias0.6%This article: 23.7%Vanshika: 7.1%dailydot.com: 7.5%Negativity Bias23.7%This article: 0.6%Vanshika: 0.5%dailydot.com: 1.0%Self-Serving Bias0.6%This article: 3.2%Vanshika: 2.5%dailydot.com: 2.2%Fundamental Attribution Error3.2%This article: 0.0%Vanshika: 0.1%dailydot.com: 0.3%Actor-Observer Bias0.0%This article: 0.0%Vanshika: 0.4%dailydot.com: 1.2%In-Group Bias0.0%This article: 0.0%Vanshika: 0.5%dailydot.com: 1.1%Out-Group Homogeneity Bias0.0%This article: 0.0%Vanshika: 0.7%dailydot.com: 1.7%Halo Effect0.0%This article: 0.0%Vanshika: 0.0%dailydot.com: 0.3%Horn Effect0.0%This article: 0.0%Vanshika: 0.0%dailydot.com: 0.0%Dunning-Kruger Effect0.0%This article: 4.6%Vanshika: 0.5%dailydot.com: 0.5%Recency Bias4.6%This article: 0.0%Vanshika: 0.3%dailydot.com: 0.3%Primacy Effect0.0%This article: 0.0%Vanshika: 0.1%dailydot.com: 0.1%Blind-Spot Bias0.0%This article: 0.0%Vanshika: 1.2%dailydot.com: 1.7%Ad Hominem0.0%This article: 0.0%Vanshika: 0.6%dailydot.com: 0.3%Straw Man0.0%This article: 1.2%Vanshika: 1.0%dailydot.com: 1.5%Appeal to Authority1.2%This article: 12.3%Vanshika: 2.5%dailydot.com: 1.8%False Dilemma12.3%This article: 0.0%Vanshika: 0.4%dailydot.com: 0.6%Slippery Slope0.0%This article: 2.8%Vanshika: 0.1%dailydot.com: 0.1%Circular Reasoning2.8%This article: 8.7%Vanshika: 6.4%dailydot.com: 7.7%Hasty Generalization8.7%This article: 1.8%Vanshika: 0.3%dailydot.com: 0.2%Red Herring1.8%This article: 9.9%Vanshika: 2.1%dailydot.com: 2.0%Bandwagon9.9%This article: 11.3%Vanshika: 4.5%dailydot.com: 5.6%Appeal to Emotion11.3%This article: 8.9%Vanshika: 0.6%dailydot.com: 0.8%Begging the Question8.9%This article: 0.0%Vanshika: 0.6%dailydot.com: 1.2%Post Hoc (False Cause)0.0%This article: 0.0%Vanshika: 0.0%dailydot.com: 0.2%Tu Quoque0.0%This article: 13.9%Vanshika: 1.3%dailydot.com: 1.5%Burden of Proof13.9%This article: 0.0%Vanshika: 0.2%dailydot.com: 0.1%Appeal to Nature0.0%This article: 0.0%Vanshika: 0.3%dailydot.com: 0.1%Composition/Division0.0%This article: 5.8%Vanshika: 6.9%dailydot.com: 6.4%Anecdotal5.8%This article: 0.0%Vanshika: 0.2%dailydot.com: 0.1%No True Scotsman0.0%This article: 10.3%Vanshika: 0.9%dailydot.com: 1.6%Ambiguity (Equivocation)10.3%This article: 0.0%Vanshika: 0.0%dailydot.com: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Vanshika: 0.3%dailydot.com: 0.2%Middle Ground0.0%This article: 3.4%Vanshika: 0.3%dailydot.com: 0.2%Personal Incredulity3.4%This article: 0.0%Vanshika: 0.1%dailydot.com: 0.1%Special Pleading0.0%This article: 0.0%Vanshika: 0.0%dailydot.com: 0.1%Genetic Fallacy0.0%This article: 39.0%Vanshika: 7.0%dailydot.com: 4.1%Unattributed Quote39.0%This article: 2.2%Vanshika: 2.2%dailydot.com: 2.7%Quote-first Misdirection2.2%This article: 3.8%Vanshika: 1.8%dailydot.com: 3.3%Biased Writer Voice3.8%This article: 0.6%Vanshika: 0.4%dailydot.com: 1.3%Indoctrination0.6%This article: 0.0%Vanshika: 0.0%dailydot.com: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Vanshika: 0.0%dailydot.com: 0.5%Politically Right Leaning Bias0.0%This article: 0.0%Vanshika: 1.9%dailydot.com: 1.6%Attempt to Sell a Product or S…0.0%

503 words analyzed.

Speakers

1speaker1.2%attributed speech497writer words
0%flagged-word coverage
6 attributed words100% of attributed speech94% writer coverage
0%20.0%40.0%Unattributed Quote-39.4 ptsWriter: 39.4%DocumentingLibs (@HistorianUSA1): 0.0%0.0%Biased Writer Voice-3.8 ptsWriter: 3.8%DocumentingLibs (@HistorianUSA1): 0.0%0.0%Quote-first Misdirection-2.2 ptsWriter: 2.2%DocumentingLibs (@HistorianUSA1): 0.0%0.0%Indoctrination-0.6 ptsWriter: 0.6%DocumentingLibs (@HistorianUSA1): 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.