Military Families Bear the Burden of War, Again ⁠34%

By Kassie Bracken⁠0% Luke Piotrowski⁠0% Caroline Kim⁠0%

4/8/2026, 7:31:42 PM

BS Summary: This article contains 30 faulty reasoning types, including Appeal to Emotion, Pessimism Bias, and Availability Heuristic, with Negativity Bias as the most egregious example at 30.3% saturation with 219 hits. Analysis detected 1,414 faulty-reasoning hits from 722 analyzed words, generating a BS Score of 42.2% and a BS Rank of ⁠34% (13,976 of 21,170 articles). This article is better (less manipulative) than 66.00% of the article peer group.

Even as a two-week ceasefire takes hold, mothers in multigenerational military families — some veterans themselves — are anxious about what the war in Iran could mean for their children, as they face the uncertainty of another conflict in the Middle East. 
KAYLA: Those are the ready-to-go care packages, I actually was going to the post office on Tuesday. 
KAYLA STEWART IS A MARINE VETERAN. 
HER DAUGHTER JULISSA IS SERVING IN THE U.S. - ISRAELI WAR IN IRAN, CURRENTLY DEPLOYED WITH THE NAVY IN BAHRAIN. 
KAYLA: …She loves harry potter so I found a harry potter tooth brush…her favorite gummies…so I got the easter version of those…….these will get to her way after Easter, unfortunately. 
KAYLA: Just seeing the world, that's what she wanted to do - see the world. 
KAYLA: And she chose the Navy. 
So I'm actually really proud of her. 
KAYLA: But // Never in a million years would I have thought I would have had a child in a war time situation. 
WE'RE IN JACKSONVILLE, NORTH CAROLINA, OUTSIDE CAMP LEJEUNE, THE LARGEST MILITARY TRAINING HUB ON THE EAST COAST. 
FOR SOME MILITARY FAMILIES HERE, WAR IN THE MIDDLE EAST IS NOW IMPACTING A SECOND GENERATION KAYLA UPSOT: She'll be happy to get when she opens those. 
KAYLA: THere's my boot camp photo. 
KAYLA: September 11th happened when I was in boot camp. //they said America's under attack. 
We didn't know what that meant, you know, you're a bunch of 18, 19 year old kids KAYLA: I pray for her safety everyday KAYLA: The Marine Corp taught me how to be numb. 
KAYLA: But at the same time, I'm a mom. 
// It takes a lot out of you. 
SCENE 2: BRUNCH SINCE THE WAR BEGAN, KAYLA HAS FOUND SUPPORT IN A GROUP OF MILITARY VETS, WIDOWS AND PARENTS OF ACTIVE DUTY SERVICEMEMBERS. 
(Group oohs and ahs in greeting) CARLA ARANA SERVED TWO TOURS IN IRAQ CARLA: It's like history repeating itself. 
CARLA: In 2003//I fought a war, for this generation t CARLA: Why are we still in the same position? 
This has been going on since 2003. 
CARLA: Why are people dying? 
CARLA: What's the value? 
And at what cost? 
CARLA: Not a lot of people know what it's like to be mortared. 
Running for your life. . 
KAYLA: …My daughter- the last known location that I knew her to be, there was a bomb, a missile strike. 
So I'm like, okay, I've been here before, I've been in the military, I know how these things work, it's radio silence right now. 
MICHELLE: That was scary. 
It still is scary. (nods with concern.) 
KAYLA: Somebody said “have you heard anything from your daughter? 
And I said, So, um. 
'No one has knocked on my door yet, so all is good." 
MASTER STRINGOUT: 3:14:05 KAYLA: And I know your son is just getting started…. 
SCENE 3: AT HOME WITH MICHELLE MICHELLE: It's war//No matter what you always have to be ready. 
//But//the iran war it's my baby. 
//If it got to a point where had to go//it would crush me. 
//I don't even want to think about it. 
MICHELLE: He wanted to make his dad proud MICHELLE WINDLE'S SON DESMOND RECENTLY ENLISTED IN THE NAVY. 
HER HUSBAND DENNIS, A MARINE, SERVED MULTIPLE DEPLOYMENTS TO THE MIDDLE EAST. 
MICHELLE: I'm a military widow. 
// That's the flag they gave me when my husband passed away. 
HE DIED AT THE AGE OF 45 FROM CANCER RELATED TO CHEMICAL EXPOSURE THERE//IN THE REGION MICHELLE: This is Dez's boot camp picture, and this is my husband's boot camp picture…They were both 18. 
MICHELLE HASN'T SEEN HER SON SINCE THE CHRISTMAS HOLIDAY. 
MICHELLE: //I said, you know what? 
//I'm just going to keep my tree up because//this is scary//we don't know what may happen//and just having it up makes me feel closer to them. 
MICHELLE: He said "mom//right now I'm safe.//but if I have to go, I have to go." -END- 1:16:51 MICHELLE: He's going to serve his county. 
And do what he can. 
MICHELLE: The Iran War.. 
I think.. 
If it got to a point that he had to go….it would crush me. 
//I don't even want to think about it. 
04:14:24 MICHELLE: We don't know what may happen. 
We don't know. 
It is scary. 
Article reasoning-pattern comparisonThis article: 6.6%Kassie Bracken: 1.9%The New York Times: 1.7%Confirmation Bias6.6%This article: 1.0%Kassie Bracken: 1.1%The New York Times: 0.4%Anchoring Bias1.0%This article: 14.4%Kassie Bracken: 9.3%The New York Times: 2.1%Availability Heuristic14.4%This article: 2.6%Kassie Bracken: 0.7%The New York Times: 0.6%Representativeness Heuristic2.6%This article: 2.1%Kassie Bracken: 2.1%The New York Times: 0.6%Hindsight Bias2.1%This article: 3.3%Kassie Bracken: 2.5%The New York Times: 2.4%Overconfidence Bias3.3%This article: 6.0%Kassie Bracken: 4.1%The New York Times: 5.8%Framing Effect6.0%This article: 6.9%Kassie Bracken: 4.2%The New York Times: 0.6%Loss Aversion6.9%This article: 5.0%Kassie Bracken: 3.1%The New York Times: 0.4%Status Quo Bias5.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%Sunk Cost Effect0.0%This article: 7.2%Kassie Bracken: 3.7%The New York Times: 2.7%Optimism Bias7.2%This article: 23.1%Kassie Bracken: 10.1%The New York Times: 3.5%Pessimism Bias23.1%This article: 30.3%Kassie Bracken: 16.6%The New York Times: 9.4%Negativity Bias30.3%This article: 0.0%Kassie Bracken: 0.5%The New York Times: 1.3%Self-Serving Bias0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.9%Fundamental Attribution Error0.0%This article: 1.2%Kassie Bracken: 0.3%The New York Times: 0.2%Actor-Observer Bias1.2%This article: 6.5%Kassie Bracken: 2.1%The New York Times: 1.1%In-Group Bias6.5%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.6%Out-Group Homogeneity Bias0.0%This article: 3.3%Kassie Bracken: 0.8%The New York Times: 0.9%Halo Effect3.3%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%Horn Effect0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.0%Dunning-Kruger Effect0.0%This article: 2.2%Kassie Bracken: 1.9%The New York Times: 1.1%Recency Bias2.2%This article: 2.4%Kassie Bracken: 0.6%The New York Times: 0.2%Primacy Effect2.4%This article: 2.2%Kassie Bracken: 0.6%The New York Times: 0.1%Blind-Spot Bias2.2%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.8%Ad Hominem0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%Straw Man0.0%This article: 5.7%Kassie Bracken: 3.2%The New York Times: 4.0%Appeal to Authority5.7%This article: 3.5%Kassie Bracken: 1.5%The New York Times: 1.2%False Dilemma3.5%This article: 1.8%Kassie Bracken: 0.5%The New York Times: 0.8%Slippery Slope1.8%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%Circular Reasoning0.0%This article: 7.2%Kassie Bracken: 3.8%The New York Times: 2.7%Hasty Generalization7.2%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%Red Herring0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.2%Bandwagon0.0%This article: 24.2%Kassie Bracken: 8.1%The New York Times: 3.4%Appeal to Emotion24.2%This article: 0.6%Kassie Bracken: 0.1%The New York Times: 0.4%Begging the Question0.6%This article: 1.0%Kassie Bracken: 1.4%The New York Times: 2.4%Post Hoc (False Cause)1.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%Tu Quoque0.0%This article: 3.3%Kassie Bracken: 1.0%The New York Times: 0.3%Burden of Proof3.3%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%Appeal to Nature0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.2%Composition/Division0.0%This article: 13.0%Kassie Bracken: 3.4%The New York Times: 1.0%Anecdotal13.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%No True Scotsman0.0%This article: 5.3%Kassie Bracken: 1.3%The New York Times: 1.8%Ambiguity (Equivocation)5.3%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%Middle Ground0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.0%Personal Incredulity0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.0%Special Pleading0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.1%Genetic Fallacy0.0%This article: 2.8%Kassie Bracken: 1.4%The New York Times: 2.1%Unattributed Quote2.8%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 1.0%Quote-first Misdirection0.0%This article: 1.1%Kassie Bracken: 2.3%The New York Times: 3.8%Biased Writer Voice1.1%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.5%Indoctrination0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.8%Politically Left Leaning Bias0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.3%Politically Right Leaning Bias0.0%This article: 0.0%Kassie Bracken: 0.0%The New York Times: 0.6%Attempt to Sell a Product or S…0.0%

722 words analyzed.

Speakers

3speakers72%attributed speech200writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 8 words • 100.0% coverageWriter's voice • 42 words • 0.0% coverageKAYLA • 17 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 20 words • 100.0% coverageKAYLA • 30 words • 0.0% coverageKAYLA • 15 words • 0.0% coverageKAYLA • 6 words • 0.0% coverageKAYLA • 7 words • 0.0% coverageKAYLA • 23 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageKAYLA • 27 words • 0.0% coverageKAYLA • 6 words • 0.0% coverageKAYLA • 15 words • 0.0% coverageKAYLA • 34 words • 0.0% coverageKAYLA • 9 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageCARLA ARANA • 19 words • 0.0% coverageCARLA ARANA • 19 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageCARLA ARANA • 5 words • 0.0% coverageCARLA ARANA • 4 words • 0.0% coverageCARLA ARANA • 4 words • 0.0% coverageCARLA ARANA • 13 words • 0.0% coverageCARLA ARANA • 5 words • 0.0% coverageKAYLA • 20 words • 0.0% coverageKAYLA • 24 words • 0.0% coverageMICHELLE • 4 words • 0.0% coverageMICHELLE • 7 words • 0.0% coverageKAYLA • 10 words • 0.0% coverageKAYLA • 5 words • 0.0% coverageKAYLA • 12 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageMICHELLE • 17 words • 0.0% coverageMICHELLE • 6 words • 0.0% coverageMICHELLE • 13 words • 0.0% coverageMICHELLE • 8 words • 0.0% coverageMICHELLE • 17 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageMICHELLE • 5 words • 0.0% coverageMICHELLE • 12 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageMICHELLE • 6 words • 0.0% coverageMICHELLE • 26 words • 0.0% coverageMICHELLE • 25 words • 0.0% coverageMICHELLE • 5 words • 0.0% coverageMICHELLE • 4 words • 0.0% coverageMICHELLE • 2 words • 0.0% coverageMICHELLE • 14 words • 0.0% coverageMICHELLE • 8 words • 0.0% coverageMICHELLE • 8 words • 0.0% coverageMICHELLE • 3 words • 0.0% coverageMICHELLE • 3 words • 0.0% coverage
Selected voice

CARLA ARANA

100%flagged-word coverage
69 attributed words13% of attributed speech85% writer coverage
0%5.0%10.0%Unattributed Quote-10.0 ptsWriter: 10.0%CARLA ARANA: 0.0%0.0%Biased Writer Voice-4.0 ptsWriter: 4.0%CARLA ARANA: 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.