Sea-Tac manages government shutdown turbulence with normal wait times and no ICE 5%

By Ruby de Luna0%

3/24/2026, 3:17:46 AM

BS Summary: This article contains 5 faulty reasoning types, including Red Herring, Anecdotal, and Framing Effect, with Appeal to Emotion as the most egregious example at 25.8% saturation with 77 hits. Analysis detected 168 faulty-reasoning hits from 298 analyzed words, generating a BS Score of 20.1% and a BS Rank of 5% (20,858 of 21,887 articles). This article is better (less manipulative) than 95.30% of the article peer group.

No ICE agents have been assigned to the SEA Airport yet, following President Donald Trump’s orders to send immigration agents to several U.S. airports to fill in for TSA agents during the ongoing partial government shutdown. 
Passenger Sharon Feucht was at SEA Airport Monday, planning to fly to France. 
She arrived early for TSA, but not just to avoid the lines. 
“We dropped off some gift cards for the TSA employees,” Feucht said. 
“I felt like we could help them a little bit… since they’re not getting paid at this time.” 
Approximately 50,000 TSA agents are working without pay for the sixth week, since a partial government shutdown in early February caused a lapse in funding for certain agencies within the Department of Homeland Security. 
Feucht dropped off grocery gift cards at the airport’s conference center. 
The Seattle airport has two two donation bins in the conference center where people can leave non-perishable food items. 
SEA Airport spokesperson Perry Cooper said the response from the community, and airport tenants have been heartfelt. 
“The thing that’s the hardest for them right now to get here, with the increase of gas prices is to get enough money to fill up their cars," Cooper said. 
Wait times at the airport have been holding steady at 15 minutes. 
Cooper said SEA has hired extra help for non-security duties like directing passengers to keep the lines moving for the last several years. 
“Trying to tell people to take things out of your pockets or make sure you’ve got water out," he said. 
"Sending people to different lines when they know that one’s shorter, those kinds of things.” 
Cooper says it also helps that a new checkpoint has been added last year. 
Article reasoning-pattern comparisonThis article: 0.0%Ruby de Luna: 0.9%KUOW: 2.6%Confirmation Bias0.0%This article: 0.0%Ruby de Luna: 1.5%KUOW: 1.3%Anchoring Bias0.0%This article: 0.0%Ruby de Luna: 2.9%KUOW: 3.4%Availability Heuristic0.0%This article: 0.0%Ruby de Luna: 1.2%KUOW: 1.2%Representativeness Heuristic0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.7%Hindsight Bias0.0%This article: 0.0%Ruby de Luna: 0.9%KUOW: 1.4%Overconfidence Bias0.0%This article: 4.0%Ruby de Luna: 5.1%KUOW: 7.4%Framing Effect4.0%This article: 0.0%Ruby de Luna: 0.3%KUOW: 1.0%Loss Aversion0.0%This article: 0.0%Ruby de Luna: 0.3%KUOW: 1.0%Status Quo Bias0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.2%Sunk Cost Effect0.0%This article: 0.0%Ruby de Luna: 2.4%KUOW: 3.8%Optimism Bias0.0%This article: 0.0%Ruby de Luna: 4.5%KUOW: 1.8%Pessimism Bias0.0%This article: 0.0%Ruby de Luna: 4.7%KUOW: 8.0%Negativity Bias0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 2.0%Self-Serving Bias0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.9%Fundamental Attribution Error0.0%This article: 0.0%Ruby de Luna: 0.8%KUOW: 0.2%Actor-Observer Bias0.0%This article: 0.0%Ruby de Luna: 0.4%KUOW: 2.0%In-Group Bias0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.5%Out-Group Homogeneity Bias0.0%This article: 0.0%Ruby de Luna: 2.3%KUOW: 2.7%Halo Effect0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.2%Horn Effect0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 1.1%Recency Bias0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.4%Primacy Effect0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.0%Blind-Spot Bias0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.5%Ad Hominem0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.3%Straw Man0.0%This article: 0.0%Ruby de Luna: 1.2%KUOW: 4.3%Appeal to Authority0.0%This article: 0.0%Ruby de Luna: 0.6%KUOW: 1.4%False Dilemma0.0%This article: 0.0%Ruby de Luna: 1.8%KUOW: 0.9%Slippery Slope0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.1%Circular Reasoning0.0%This article: 0.0%Ruby de Luna: 1.5%KUOW: 4.1%Hasty Generalization0.0%This article: 12.4%Ruby de Luna: 0.9%KUOW: 0.3%Red Herring12.4%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.8%Bandwagon0.0%This article: 25.8%Ruby de Luna: 4.7%KUOW: 6.1%Appeal to Emotion25.8%This article: 0.0%Ruby de Luna: 0.8%KUOW: 0.8%Begging the Question0.0%This article: 0.0%Ruby de Luna: 4.1%KUOW: 2.2%Post Hoc (False Cause)0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.1%Tu Quoque0.0%This article: 0.0%Ruby de Luna: 0.1%KUOW: 0.3%Burden of Proof0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.2%Appeal to Nature0.0%This article: 0.0%Ruby de Luna: 1.0%KUOW: 0.2%Composition/Division0.0%This article: 10.1%Ruby de Luna: 3.9%KUOW: 3.3%Anecdotal10.1%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.1%No True Scotsman0.0%This article: 0.0%Ruby de Luna: 2.7%KUOW: 1.4%Ambiguity (Equivocation)0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.1%Middle Ground0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.1%Personal Incredulity0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.2%Special Pleading0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.2%Genetic Fallacy0.0%This article: 0.0%Ruby de Luna: 1.1%KUOW: 1.0%Unattributed Quote0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 0.8%Quote-first Misdirection0.0%This article: 0.0%Ruby de Luna: 1.9%KUOW: 3.2%Biased Writer Voice0.0%This article: 0.0%Ruby de Luna: 0.7%KUOW: 1.5%Indoctrination0.0%This article: 4.0%Ruby de Luna: 1.1%KUOW: 1.1%Politically Left Leaning Bias4.0%This article: 0.0%Ruby de Luna: 1.6%KUOW: 0.2%Politically Right Leaning Bias0.0%This article: 0.0%Ruby de Luna: 0.0%KUOW: 1.3%Attempt to Sell a Product or S…0.0%

298 words analyzed.

Speakers

2speakers50%attributed speech149writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 100.0% coverageWriter's voice • 36 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageSharon Feucht • 12 words • 0.0% coverageSharon Feucht • 18 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 19 words • 0.0% coveragePerry Cooper • 17 words • 0.0% coveragePerry Cooper • 30 words • 0.0% coverageWriter's voice • 12 words • 0.0% coveragePerry Cooper • 23 words • 0.0% coveragePerry Cooper • 20 words • 0.0% coveragePerry Cooper • 15 words • 0.0% coveragePerry Cooper • 14 words • 0.0% coverage
Selected voice

Sharon Feucht

100%flagged-word coverage
30 attributed words20% of attributed speech8.1% writer coverage
0%5.0%10.0%Politically Left Leaning B-8.1 ptsWriter: 8.1%Sharon Feucht: 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.