WDIV17%

Ex-boyfriend who pleaded guilty to murdering Detroit teen London Thomas learns sentence 16%

By Samantha Sayles18% Jay Scott Smith37% Richard Estrada12%

7/31/2026, 9:08:42 AM

BS Summary: This article contains 11 faulty reasoning types, including Negativity Bias, Biased Writer Voice, and Pessimism Bias, with Appeal to Emotion as the most egregious example at 21.2% saturation with 117 hits. Analysis detected 377 faulty-reasoning hits from 551 analyzed words, generating a BS Score of 24.2% and a BS Rank of 16% (25,940 of 30,584 articles). This article is better (less manipulative) than 84.80% of the article peer group.

WAYNE COUNTY, Mich.  Jalen Pendergrass, the young man who admitted to killing his ex-girlfriend, London Thomas, will serve 25 to 50 years in prison. 
Pendergrass was sentenced on Friday morning after pleading guilty to second-degree murder on July 2, while all other charges against him were dropped. 
“The sentence agreement is for Mr. 
Pendergrass to serve a maximum of 50 years in the Michigan Department of Corrections and a minimum of 25 years,” Judge Paul Cusic said on Friday morning. 
“I do believe that every minute of a 50-year sentence would be deserved in this case.” 
Pendergrass admitted to strangling Thomas to death during an altercation at his home on Carlysle Street in Inkster on April 5, 2025. 
The 23-year-old Pendergrass and the 17-year-old Thomas had been in a relationship, but it had ended by the time she arrived at the house. 
Thomas was found dead three weeks later in Southfield on April 26, 2025  two weeks after she had been reported missing to the Detroit Police. 
Pendergrass was charged alongside his 49-year-old mother, Charla. 
It was one of her friends who told the FBI that she asked him to move the plastic bin that unknowingly contained London’s body. 
“This case is different than some of the other ones that I had,” Dominic DeGrazia, the Prosecuting Attorney, said during the sentencing. 
“To the extent that the defendant’s pattern of deception and cold-blooded, cold-heartedness in this case really stands out.” 
‘A Waste of Skin’ 
The family’s pain was on full display in the courtroom this morning. 
Both of Thomas’ grandmothers, along with Jasma Bennett, Thomas’ mother, gave jarring impact statements. 
“I ain’t never been able to have animosity in my heart for nobody,” Jestina Martin said. 
“But I do for you, because you took a part of my life that never be filled.” 
“You took a piece of me,” she said. 
“Whatever you get, it’s what you deserve.” 
Meanwhile, Barbara Bennett, Thomas’ maternal grandmother, attempted to show grace in mourning London but took a pointed shot at both mother and son for what they had done. 
“I will always love London, always, until we meet again,” Bennett said. 
“The only regret that I have is that Charla and Jalen Pendergrass are still walking this Earth, and London is not. 
He is a waste of skin!” 
London’s mother spoke through tears on the stand, saying that she has not known peace since her daughter was taken from her. 
She quoted Bible verses and shared stories of missing the simple moments with her daughter. 
“There is not a moment that you are not in my thoughts and prayers,” Jasma Bennett said. 
“She had such a strong and beautiful, truthful, brave, fearless personality and energy. 
“As I wake and when I sleep and when I try to live, this devastation will never, ever leave me,” she added. 
“We would try, try to keep going. 
She didn’t even have the opportunity to argue and fight and then to make it right.” 
Jalen Pendergrass is off to prison; this case is not fully closed. 
Charla Pendergrass is still facing first-degree murder, unlawful imprisonment and evidence tampering charges. 
Her trial will begin on Oct. 
26. 
You can listen to the full sentencing hearing below: 
Article reasoning-pattern comparisonThis article: 0.0%Samantha Sayles: 0.3%WDIV: 2.2%Confirmation Bias0.0%This article: 0.0%Samantha Sayles: 0.2%WDIV: 0.7%Anchoring Bias0.0%This article: 4.4%Samantha Sayles: 0.9%WDIV: 1.9%Availability Heuristic4.4%This article: 0.0%Samantha Sayles: 0.2%WDIV: 0.6%Representativeness Heuristic0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.4%Hindsight Bias0.0%This article: 0.0%Samantha Sayles: 0.2%WDIV: 0.7%Overconfidence Bias0.0%This article: 0.0%Samantha Sayles: 0.3%WDIV: 2.4%Framing Effect0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.4%Loss Aversion0.0%This article: 0.0%Samantha Sayles: 0.1%WDIV: 0.4%Status Quo Bias0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Sunk Cost Effect0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 1.5%Optimism Bias0.0%This article: 6.9%Samantha Sayles: 1.1%WDIV: 0.6%Pessimism Bias6.9%This article: 16.2%Samantha Sayles: 4.0%WDIV: 4.3%Negativity Bias16.2%This article: 2.9%Samantha Sayles: 0.2%WDIV: 0.5%Self-Serving Bias2.9%This article: 0.0%Samantha Sayles: 0.7%WDIV: 0.4%Fundamental Attribution Error0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.1%Actor-Observer Bias0.0%This article: 2.4%Samantha Sayles: 0.2%WDIV: 0.3%In-Group Bias2.4%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Out-Group Homogeneity Bias0.0%This article: 0.0%Samantha Sayles: 1.3%WDIV: 1.6%Halo Effect0.0%This article: 0.0%Samantha Sayles: 0.1%WDIV: 0.0%Horn Effect0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Samantha Sayles: 0.1%WDIV: 0.6%Recency Bias0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.2%Primacy Effect0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Blind-Spot Bias0.0%This article: 1.1%Samantha Sayles: 0.2%WDIV: 0.1%Ad Hominem1.1%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.1%Straw Man0.0%This article: 0.0%Samantha Sayles: 5.0%WDIV: 3.0%Appeal to Authority0.0%This article: 2.2%Samantha Sayles: 0.8%WDIV: 0.5%False Dilemma2.2%This article: 0.0%Samantha Sayles: 0.3%WDIV: 0.1%Slippery Slope0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.1%Circular Reasoning0.0%This article: 0.0%Samantha Sayles: 0.1%WDIV: 1.2%Hasty Generalization0.0%This article: 0.0%Samantha Sayles: 0.1%WDIV: 0.0%Red Herring0.0%This article: 0.0%Samantha Sayles: 0.2%WDIV: 0.3%Bandwagon0.0%This article: 21.2%Samantha Sayles: 9.8%WDIV: 4.4%Appeal to Emotion21.2%This article: 0.0%Samantha Sayles: 0.2%WDIV: 0.3%Begging the Question0.0%This article: 2.9%Samantha Sayles: 0.5%WDIV: 1.2%Post Hoc (False Cause)2.9%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.1%Tu Quoque0.0%This article: 0.0%Samantha Sayles: 0.4%WDIV: 0.5%Burden of Proof0.0%This article: 0.0%Samantha Sayles: 0.5%WDIV: 0.1%Appeal to Nature0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Composition/Division0.0%This article: 0.0%Samantha Sayles: 0.5%WDIV: 1.7%Anecdotal0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%No True Scotsman0.0%This article: 0.0%Samantha Sayles: 0.4%WDIV: 0.9%Ambiguity (Equivocation)0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Middle Ground0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Personal Incredulity0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Special Pleading0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Genetic Fallacy0.0%This article: 1.1%Samantha Sayles: 2.4%WDIV: 1.5%Unattributed Quote1.1%This article: 0.0%Samantha Sayles: 0.9%WDIV: 0.8%Quote-first Misdirection0.0%This article: 7.3%Samantha Sayles: 0.7%WDIV: 1.4%Biased Writer Voice7.3%This article: 0.0%Samantha Sayles: 2.3%WDIV: 1.5%Indoctrination0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Samantha Sayles: 0.0%WDIV: 0.0%Politically Right Leaning Bias0.0%This article: 0.0%Samantha Sayles: 0.3%WDIV: 1.2%Attempt to Sell a Product or S…0.0%

551 words analyzed.

Speakers

6speakers51%attributed speech269writer words
Selected voice

Jasma Bennett

91%flagged-word coverage
75 attributed words27% of attributed speech32% writer coverage
0%7.5%15.0%Biased Writer Voice-14.9 ptsWriter: 14.9%Jasma Bennett: 0.0%0.0%Unattributed Quote-2.2 ptsWriter: 2.2%Jasma Bennett: 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.