MS NOW95%

Jennifer Lopez’s ‘Subway Takes’ appearance masks a troubling message 83%

By Noor Noman0%

6/8/2026, 9:15:20 PM

BS Summary: This article contains 31 faulty reasoning types, including Politically Right Leaning Bias, Confirmation Bias, and Hasty Generalization, with Negativity Bias as the most egregious example at 40.2% saturation with 337 hits. Analysis detected 2,791 faulty-reasoning hits from 839 analyzed words, generating a BS Score of 74.6% and a BS Rank of 83% (3,706 of 21,168 articles). This article is worse (more manipulative) than 82.50% of the article peer group.

Jennifer Lopez was the most recent big-name celebrity to join comedian Kareem Rahma for his viral social media video series, “Subway Takes.” 
Her thesis statement, or take: “You have to be born in New York to be a New Yorker.” 
Rahma suitably responded with a loud groan. 
“I know everybody wants to claim our city, but you have to be born in New York,” she says. 
“You have to be born in one of the five boroughs to be a New Yorker.” 
On its face, perhaps in a different time and political climate, this could masquerade as a certain well-worn pride New Yorkers love to claim and argue about. 
But in reality it’s tone-deaf at best and nativist at worst. 
What makes New York such a special, dynamic, vibrant and multicultural place is precisely that it is a city of immigrants. 
Using words like “our” reinforces the idea of an in-group and an out-group  the very premise of a political administration that has made no secret about who it says “belongs” in this country and who does not. 
It is a major building block of the fascistic and autocratic political ideologies increasingly taking hold both here and around the world, and it’s central to the worldview espoused by President Donald Trump and MAGA supporters. 
We’re seeing what happens when someone draws a line determining who belongs and who doesn’t. 
Trump’s rhetoric often deploys words and phrases such as “invasion” and “occupied country.” 
At a rally in Colorado in 2024, Trump said: “People come in, they’re very sick. 
Very sick. 
They’re coming into our country, they’re very, very sick with highly contagious disease. 
And they’re let into our country to infect our country.” 
There is a strong sense in Trump’s America that some people (read: white people) truly belong, that they are real Americans while everyone else is an invader. 
What makes New York such a special, dynamic, vibrant and multicultural place is precisely that it is a city of immigrants. 
New York Mayor Zohran Mamdani (notably, not born in New York, like so many immigrants who call the city home) noted this during his fiery acceptance speech in November when he pledged, “New York will remain a city of immigrants, built by immigrants, powered by immigrants.” 
Throughout his campaign, he both identified and celebrated what is best about the city: It is a melting pot in which anyone and everyone is welcome, a place they can call home. 
The same could be said about this country as a whole, which was founded by immigrants. 
The political project of America is, of course, a complicated one, and in many ways an inherently violent one  but, again, at its best, it is a melting pot of cultures, languages and traditions, a home for people seeking new opportunities. 
While likely unintentional, Lopez is reproducing rhetoric similar to MAGA and other right-wing political movements by espousing an in-group/out-group mentality in which identity (and therefore acceptance) is tied to borders. 
Immigrants and “outsiders” have been made incredibly vulnerable under the current administration. 
While likely unintentional, Lopez is reproducing rhetoric similar to MAGA and other right-wing political movements by espousing an in-group/out-group mentality. 
A very intentional version of this argument (that you can only claim an identity if you were born here) was part of what sparked a wave of xenophobia against the Haitian community in Springfield, Ohio, in 2024. 
It played a part in justifying the government targeting Somalis in Minnesota. 
Violent raids from Immigration and Customs Enforcement have created fear in immigrant communities across the country. 
People held in ICE custody, including children and people with special needs, are experiencing horrific conditions and are denied basic rights. 
These inhumane conditions include, for example, food with worms in it and bright fluorescent lights turned on 24/7. 
Some people have been deported to countries they have no connection to. 
Lopez, who does not reside in New York but in a reported $18 million property in the gated Hidden Hills community in Los Angeles, has been a vocal Democratic supporter, endorsing Kamala Harris in the last general election and publicly deriding Trump for his comments on Puerto Rico. 
Partaking in and reproducing this fundamentally right-wing narrative (again, even if it’s unintentional) flies in the face of what Democrats ostensibly stand for  that there is a big tent under which everyone is welcome and belongs. 
The New York City subway  the site of this interview  is a perfect metaphor for New Yorkers and what New York represents at its best. 
A subway is a democratic and equalizing space, welcome to all irrespective of where you’re from. 
There is a transience to it; people stay on for varying lengths of time, but they are equals for the time they ride next to each other. 
These are all antithetical ideas to Lopez’s apparent logic on “Subway Takes.” 
Because, sadly, according to JLo, you can only really be from the block if you’re born on it. 
Article reasoning-pattern comparisonThis article: 24.0%Noor Noman: 12.3%MS NOW: 7.5%Confirmation Bias24.0%This article: 0.0%Noor Noman: 0.3%MS NOW: 1.2%Anchoring Bias0.0%This article: 13.1%Noor Noman: 8.8%MS NOW: 3.7%Availability Heuristic13.1%This article: 10.1%Noor Noman: 1.2%MS NOW: 1.1%Representativeness Heuristic10.1%This article: 0.0%Noor Noman: 0.4%MS NOW: 1.3%Hindsight Bias0.0%This article: 0.0%Noor Noman: 0.0%MS NOW: 2.6%Overconfidence Bias0.0%This article: 4.3%Noor Noman: 12.3%MS NOW: 15.5%Framing Effect4.3%This article: 0.0%Noor Noman: 0.5%MS NOW: 0.7%Loss Aversion0.0%This article: 0.0%Noor Noman: 0.0%MS NOW: 0.9%Status Quo Bias0.0%This article: 0.0%Noor Noman: 0.0%MS NOW: 0.1%Sunk Cost Effect0.0%This article: 10.7%Noor Noman: 1.5%MS NOW: 2.4%Optimism Bias10.7%This article: 11.3%Noor Noman: 5.6%MS NOW: 3.2%Pessimism Bias11.3%This article: 40.2%Noor Noman: 23.1%MS NOW: 19.3%Negativity Bias40.2%This article: 5.7%Noor Noman: 4.4%MS NOW: 2.4%Self-Serving Bias5.7%This article: 9.3%Noor Noman: 5.3%MS NOW: 3.1%Fundamental Attribution Error9.3%This article: 0.0%Noor Noman: 0.9%MS NOW: 0.3%Actor-Observer Bias0.0%This article: 13.6%Noor Noman: 8.3%MS NOW: 3.5%In-Group Bias13.6%This article: 3.2%Noor Noman: 1.4%MS NOW: 2.6%Out-Group Homogeneity Bias3.2%This article: 13.7%Noor Noman: 1.9%MS NOW: 2.2%Halo Effect13.7%This article: 0.0%Noor Noman: 2.3%MS NOW: 1.8%Horn Effect0.0%This article: 0.0%Noor Noman: 0.0%MS NOW: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Noor Noman: 0.1%MS NOW: 1.8%Recency Bias0.0%This article: 3.2%Noor Noman: 0.3%MS NOW: 0.6%Primacy Effect3.2%This article: 0.0%Noor Noman: 0.0%MS NOW: 0.2%Blind-Spot Bias0.0%This article: 13.3%Noor Noman: 8.1%MS NOW: 4.7%Ad Hominem13.3%This article: 7.4%Noor Noman: 2.6%MS NOW: 1.3%Straw Man7.4%This article: 9.9%Noor Noman: 5.8%MS NOW: 5.4%Appeal to Authority9.9%This article: 3.2%Noor Noman: 4.0%MS NOW: 2.2%False Dilemma3.2%This article: 4.3%Noor Noman: 2.2%MS NOW: 2.2%Slippery Slope4.3%This article: 0.0%Noor Noman: 0.4%MS NOW: 0.2%Circular Reasoning0.0%This article: 23.2%Noor Noman: 15.1%MS NOW: 8.1%Hasty Generalization23.2%This article: 0.0%Noor Noman: 0.6%MS NOW: 0.7%Red Herring0.0%This article: 0.0%Noor Noman: 1.2%MS NOW: 0.9%Bandwagon0.0%This article: 9.4%Noor Noman: 16.6%MS NOW: 9.8%Appeal to Emotion9.4%This article: 0.0%Noor Noman: 2.7%MS NOW: 2.4%Begging the Question0.0%This article: 14.1%Noor Noman: 6.7%MS NOW: 3.2%Post Hoc (False Cause)14.1%This article: 0.0%Noor Noman: 1.5%MS NOW: 0.6%Tu Quoque0.0%This article: 0.0%Noor Noman: 0.5%MS NOW: 0.9%Burden of Proof0.0%This article: 0.0%Noor Noman: 0.0%MS NOW: 0.1%Appeal to Nature0.0%This article: 5.0%Noor Noman: 1.2%MS NOW: 0.3%Composition/Division5.0%This article: 6.6%Noor Noman: 2.1%MS NOW: 2.6%Anecdotal6.6%This article: 6.3%Noor Noman: 1.4%MS NOW: 0.2%No True Scotsman6.3%This article: 7.5%Noor Noman: 2.5%MS NOW: 1.7%Ambiguity (Equivocation)7.5%This article: 0.0%Noor Noman: 0.0%MS NOW: 0.0%Gambler’s Fallacy0.0%This article: 5.0%Noor Noman: 0.4%MS NOW: 0.1%Middle Ground5.0%This article: 0.0%Noor Noman: 0.5%MS NOW: 0.3%Personal Incredulity0.0%This article: 0.0%Noor Noman: 0.1%MS NOW: 0.3%Special Pleading0.0%This article: 0.0%Noor Noman: 1.4%MS NOW: 1.3%Genetic Fallacy0.0%This article: 0.0%Noor Noman: 0.1%MS NOW: 2.5%Unattributed Quote0.0%This article: 2.1%Noor Noman: 0.9%MS NOW: 1.5%Quote-first Misdirection2.1%This article: 14.5%Noor Noman: 23.4%MS NOW: 14.2%Biased Writer Voice14.5%This article: 5.2%Noor Noman: 2.6%MS NOW: 2.1%Indoctrination5.2%This article: 0.0%Noor Noman: 6.6%MS NOW: 5.3%Politically Left Leaning Bias0.0%This article: 27.3%Noor Noman: 2.2%MS NOW: 0.6%Politically Right Leaning Bias27.3%This article: 5.7%Noor Noman: 0.7%MS NOW: 0.4%Attempt to Sell a Product or S…5.7%

839 words analyzed.

Speakers

3speakers18%attributed speech686writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 9 words • 100.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 18 words • 100.0% coverageWriter's voice • 7 words • 100.0% coverageJennifer Lopez • 19 words • 100.0% coverageJennifer Lopez • 16 words • 100.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 11 words • 100.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 38 words • 100.0% coverageWriter's voice • 36 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 13 words • 100.0% coverageDonald Trump • 15 words • 0.0% coverageDonald Trump • 2 words • 0.0% coverageDonald Trump • 13 words • 0.0% coverageDonald Trump • 10 words • 0.0% coverageWriter's voice • 27 words • 100.0% coverageWriter's voice • 21 words • 0.0% coverageZohran Mamdani • 46 words • 0.0% coverageZohran Mamdani • 32 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 42 words • 0.0% coverageWriter's voice • 30 words • 100.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 20 words • 100.0% coverageWriter's voice • 37 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 16 words • 100.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 48 words • 100.0% coverageWriter's voice • 37 words • 100.0% coverageWriter's voice • 27 words • 100.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 18 words • 100.0% coverage
Selected voice

Jennifer Lopez

100%flagged-word coverage
35 attributed words23% of attributed speech97% writer coverage
0%50.0%100.0%Indoctrination+98.7 ptsWriter: 1.3%Jennifer Lopez: 100.0%100.0%Politically Right Leaning -33.4 ptsWriter: 33.4%Jennifer Lopez: 0.0%0.0%Biased Writer Voice-17.8 ptsWriter: 17.8%Jennifer Lopez: 0.0%0.0%Attempt to Sell a Product -7.0 ptsWriter: 7.0%Jennifer Lopez: 0.0%0.0%Quote-first Misdirection-2.6 ptsWriter: 2.6%Jennifer Lopez: 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.