BS Summary: This article contains 17 faulty reasoning types, including Framing Effect, Biased Writer Voice, and Representativeness Heuristic, with Hasty Generalization as the most egregious example at 17.9% saturation with 93 hits. Analysis detected 592 faulty-reasoning hits from 519 analyzed words, generating a BS Score of 32.4% and a BS Rank of 17% (18,288 of 21,887 articles). This article is better (less manipulative) than 83.60% of the article peer group.

Gov. 
Ned Lamont and his top public safety official acknowledged Friday the presence of federal ICE agents at Bradley International Airport without being able to say if it signaled a new emphasis on immigration enforcement by the Trump administration in Connecticut. 
“We were made aware that they are at the airport, and if someone goes through TSA, that they may be checked. 
And if in fact there’s a violation, that they’re pulled out of the line,” said Ronnell Higgins, the commissioner of emergency services and public protection. 
“But that’s the extent to what I know right now.” 
The media offices of ICE in New England and nationally did not respond to a request for comment. 
Connecticut is one of the blue states where immigration enforcement is a source of chronic conflict, given the passage of revisions to Trust Act that set explicit limits on the circumstances in which local enforcement can cooperate with the Immigration and Customs Enforcement agency. 
“Connecticut State Police is assigned to Bradley Airport. 
They are not involved in any way” in the immigration enforcement there, Higgins said. 
Higgins said ICE officially notified the state of its presence without sharing details on long-range plans. 
The federal agency does not routinely notify state police of arrests at the airport, a state-owned facility with federal oversight. 
“I have no reason to believe that they’re going to not be there tomorrow or the next day or the next day,” Higgins said. 
Lamont on Friday repeated the message he has been articulating since the opening of the General Assembly session in February. 
“Leave us alone. 
Leave these people alone,” he said. 
“These are maybe people who want to go for a long weekend and see the aunt in Chicago, instead of getting picked up by ICE, the TSA at Bradley, maybe sent away to a detention facility. 
I don’t want to jump to conclusions. 
We’ll see what’s happening.” 
State authorities could not confirm if anyone was arrested and detained at the airport by ICE. 
The Connecticut Airport Authority released a statement about the ICE presence late Friday. 
“The CAA has been made aware that ICE agents have conducted several targeted operations in recent weeks at Bradley International Airport,” the statement reads. 
“The federal agents involved wore plain clothes and were not readily identifiable as ICE agents. 
ICE appears to be carrying out similar operations at airports across the country. 
The CAA did not assist in these operations in any way and has learned of them only after the fact. 
“The CAA has no authority to intervene or prevent such operations, which occurred predominantly in areas under the control of the federal government,” the statement continues. 
“The mission of the CAA is to provide the safest and most convenient facilities for our workforce and the many families and individuals traveling through Bradley International Airport, and this initiative does not further that mission.” 
TRAC, the Transactional Records Access Clearinghouse, reported that more than 65,000 people were in immigration detention nationally as of July 11 and that 70% were individuals without criminal convictions. 
Article reasoning-pattern comparisonThis article: 3.1%Mark Pazniokas: 2.9%CT Mirror: 2.6%Confirmation Bias3.1%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.6%Anchoring Bias0.0%This article: 2.5%Mark Pazniokas: 1.7%CT Mirror: 3.0%Availability Heuristic2.5%This article: 8.5%Mark Pazniokas: 1.2%CT Mirror: 1.0%Representativeness Heuristic8.5%This article: 0.0%Mark Pazniokas: 0.4%CT Mirror: 0.3%Hindsight Bias0.0%This article: 0.0%Mark Pazniokas: 1.4%CT Mirror: 1.3%Overconfidence Bias0.0%This article: 15.8%Mark Pazniokas: 8.2%CT Mirror: 5.3%Framing Effect15.8%This article: 0.0%Mark Pazniokas: 0.2%CT Mirror: 0.7%Loss Aversion0.0%This article: 0.0%Mark Pazniokas: 0.3%CT Mirror: 0.6%Status Quo Bias0.0%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.3%Sunk Cost Effect0.0%This article: 5.4%Mark Pazniokas: 1.7%CT Mirror: 3.1%Optimism Bias5.4%This article: 6.9%Mark Pazniokas: 0.8%CT Mirror: 1.9%Pessimism Bias6.9%This article: 8.5%Mark Pazniokas: 7.5%CT Mirror: 7.1%Negativity Bias8.5%This article: 0.0%Mark Pazniokas: 4.5%CT Mirror: 2.1%Self-Serving Bias0.0%This article: 0.0%Mark Pazniokas: 0.9%CT Mirror: 0.5%Fundamental Attribution Error0.0%This article: 0.0%Mark Pazniokas: 0.4%CT Mirror: 0.1%Actor-Observer Bias0.0%This article: 0.0%Mark Pazniokas: 0.9%CT Mirror: 1.0%In-Group Bias0.0%This article: 0.0%Mark Pazniokas: 0.3%CT Mirror: 0.2%Out-Group Homogeneity Bias0.0%This article: 6.9%Mark Pazniokas: 5.3%CT Mirror: 1.2%Halo Effect6.9%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.0%Horn Effect0.0%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.0%Dunning-Kruger Effect0.0%This article: 3.9%Mark Pazniokas: 0.8%CT Mirror: 0.8%Recency Bias3.9%This article: 1.9%Mark Pazniokas: 0.3%CT Mirror: 0.4%Primacy Effect1.9%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.0%Blind-Spot Bias0.0%This article: 0.0%Mark Pazniokas: 2.1%CT Mirror: 1.0%Ad Hominem0.0%This article: 0.0%Mark Pazniokas: 0.6%CT Mirror: 0.3%Straw Man0.0%This article: 0.0%Mark Pazniokas: 4.0%CT Mirror: 3.5%Appeal to Authority0.0%This article: 0.0%Mark Pazniokas: 0.8%CT Mirror: 1.5%False Dilemma0.0%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.8%Slippery Slope0.0%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.1%Circular Reasoning0.0%This article: 17.9%Mark Pazniokas: 3.7%CT Mirror: 4.0%Hasty Generalization17.9%This article: 0.0%Mark Pazniokas: 0.8%CT Mirror: 0.1%Red Herring0.0%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.7%Bandwagon0.0%This article: 1.2%Mark Pazniokas: 5.0%CT Mirror: 5.2%Appeal to Emotion1.2%This article: 0.0%Mark Pazniokas: 1.7%CT Mirror: 0.8%Begging the Question0.0%This article: 0.0%Mark Pazniokas: 1.0%CT Mirror: 2.1%Post Hoc (False Cause)0.0%This article: 0.0%Mark Pazniokas: 0.2%CT Mirror: 0.2%Tu Quoque0.0%This article: 3.1%Mark Pazniokas: 2.2%CT Mirror: 0.7%Burden of Proof3.1%This article: 0.0%Mark Pazniokas: 0.3%CT Mirror: 0.1%Appeal to Nature0.0%This article: 0.0%Mark Pazniokas: 0.3%CT Mirror: 0.2%Composition/Division0.0%This article: 0.0%Mark Pazniokas: 1.2%CT Mirror: 2.7%Anecdotal0.0%This article: 0.0%Mark Pazniokas: 0.3%CT Mirror: 0.1%No True Scotsman0.0%This article: 7.7%Mark Pazniokas: 3.2%CT Mirror: 1.8%Ambiguity (Equivocation)7.7%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Mark Pazniokas: 0.5%CT Mirror: 0.2%Middle Ground0.0%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.0%Personal Incredulity0.0%This article: 6.9%Mark Pazniokas: 0.4%CT Mirror: 0.2%Special Pleading6.9%This article: 0.0%Mark Pazniokas: 0.0%CT Mirror: 0.2%Genetic Fallacy0.0%This article: 4.0%Mark Pazniokas: 1.4%CT Mirror: 0.8%Unattributed Quote4.0%This article: 0.0%Mark Pazniokas: 2.2%CT Mirror: 1.1%Quote-first Misdirection0.0%This article: 9.8%Mark Pazniokas: 2.4%CT Mirror: 2.8%Biased Writer Voice9.8%This article: 0.0%Mark Pazniokas: 0.9%CT Mirror: 2.7%Indoctrination0.0%This article: 0.0%Mark Pazniokas: 0.6%CT Mirror: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Mark Pazniokas: 1.0%CT Mirror: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Mark Pazniokas: 0.6%CT Mirror: 0.6%Attempt to Sell a Product or S…0.0%

519 words analyzed.

Speakers

4speakers65%attributed speech182writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 10 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 40 words • 0.0% coverageRonnell Higgins • 21 words • 100.0% coverageRonnell Higgins • 25 words • 0.0% coverageRonnell Higgins • 10 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 44 words • 100.0% coverageRonnell Higgins • 8 words • 0.0% coverageRonnell Higgins • 14 words • 0.0% coverageRonnell Higgins • 16 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageRonnell Higgins • 24 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageNed Lamont • 3 words • 0.0% coverageNed Lamont • 6 words • 0.0% coverageNed Lamont • 36 words • 0.0% coverageNed Lamont • 7 words • 100.0% coverageNed Lamont • 4 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageConnecticut Airport Authority • 24 words • 0.0% coverageConnecticut Airport Authority • 15 words • 0.0% coverageConnecticut Airport Authority • 13 words • 0.0% coverageConnecticut Airport Authority • 20 words • 0.0% coverageConnecticut Airport Authority • 26 words • 0.0% coverageConnecticut Airport Authority • 36 words • 0.0% coverageTRAC, the Transactional Records Access Clearinghouse • 29 words • 0.0% coverage
Selected voice

Ned Lamont

95%flagged-word coverage
56 attributed words17% of attributed speech66% writer coverage
0%12.5%25.0%Biased Writer Voice-11.7 ptsWriter: 24.2%Ned Lamont: 12.5%12.5%

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.