Boston federal judge bars Trump administration from using obscure clause to make huge funding cuts 75%

By MICHAEL CASEY13% Associated Press60%

7/17/2026, 12:51:50 PM

BS Summary: This article contains 10 faulty reasoning types, including Negativity Bias, Pessimism Bias, and Framing Effect, with Appeal to Emotion as the most egregious example at 37.9% saturation with 187 hits. Analysis detected 802 faulty-reasoning hits from 494 analyzed words, generating a BS Score of 66.7% and a BS Rank of 75% (5,571 of 21,887 articles). This article is worse (more manipulative) than 74.50% of the article peer group.

BOSTON (AP)  A federal judge in Boston on Friday ruled the Trump administration can’t use an obscure clause relating to agency priorities to make billions of dollars in funding cuts. 
Twenty-three states had a filed a lawsuit last year accusing the administration of using the clause to make cuts to everything from crime prevention to food security to scientific research. 
They were concerned that it would be used to cancel current and future grants. 
U.S. 
District Judge Indira Talwani granted a summary judgment preventing the administration from relying on the clause to make cuts and denied a motion by the government to dismiss the case. 
“Defendants’ interpretation of the Termination Clause is not clearly supported by the text of the provision, runs counter to the regulatory scheme, receives no support in the rulemaking history, and would violate the Spending Clause’s requirement that conditions be imposed unambiguously,” Talwani, who was nominated by Democratic President Barack Obama, wrote. 
The lawsuit argued that the Office of Management and Budget promulgated the use of the clause in question to justify what it described as a “nationwide slash-and-burn campaign.” 
The clause, which was first introduced in 2020 and revised in 2024, says federal agents can terminate a grant if the award “no longer effectuates the program goals or agency priorities.” 
The states argued that the language, put in place during the Biden administration, was for the first time being used to terminate grants. 
“Instead of working with us to keep the public safe and lower costs for hardworking New Jerseyans, the Trump Administration has recklessly and illegally gutted federal funding for public safety, disaster preparedness, scientific research, clean water, and more,” New Jersey Attorney General Jennifer Davenport said in a statement. 
“Today’s decision is an important win for all New Jerseyans and confirms that the Trump Administration defied the law when it embarked on its campaign to gut critical federal funding to the states,” she continued. 
“The President and his allies cannot hold critical programs hostage to their personal whims and political ideologies, destabilizing the country by yanking essential federal funding that was already awarded to the states.” 
Calling the case an “extraordinarily unusual lawsuit,” lawyers for federal government argued it should be dismissed because some of those grants have already been terminated and plaintiffs’ argument about the impact to future grants was far too speculative. 
They also accused the states of “raising blanket, undifferentiated objections” to the termination of thousands of grants without seeking relief that would “restore a single grant.” 
“That mismatch between the allegedly unlawful agency ‘decision’ on one hand, and the amorphous relief requested in this suit, on the other, creates a set of jurisdiction and justiciability defects that doom this lawsuit at the threshold,” lawyers wrote in the motion to dismiss. 
A spokesperson for the Office of Management and Budget did not respond to a request for comment. 
Article reasoning-pattern comparisonThis article: 0.0%Michael Casey: 2.1%Boston.com: 2.2%Confirmation Bias0.0%This article: 0.0%Michael Casey: 0.3%Boston.com: 1.0%Anchoring Bias0.0%This article: 0.0%Michael Casey: 2.4%Boston.com: 3.0%Availability Heuristic0.0%This article: 0.0%Michael Casey: 0.4%Boston.com: 0.7%Representativeness Heuristic0.0%This article: 0.0%Michael Casey: 0.6%Boston.com: 0.4%Hindsight Bias0.0%This article: 0.0%Michael Casey: 1.0%Boston.com: 1.4%Overconfidence Bias0.0%This article: 19.0%Michael Casey: 7.3%Boston.com: 5.7%Framing Effect19.0%This article: 0.0%Michael Casey: 0.8%Boston.com: 0.8%Loss Aversion0.0%This article: 0.0%Michael Casey: 0.1%Boston.com: 0.5%Status Quo Bias0.0%This article: 0.0%Michael Casey: 0.0%Boston.com: 0.1%Sunk Cost Effect0.0%This article: 0.0%Michael Casey: 2.6%Boston.com: 2.0%Optimism Bias0.0%This article: 23.9%Michael Casey: 2.1%Boston.com: 1.2%Pessimism Bias23.9%This article: 36.8%Michael Casey: 7.8%Boston.com: 6.2%Negativity Bias36.8%This article: 9.7%Michael Casey: 1.1%Boston.com: 1.0%Self-Serving Bias9.7%This article: 0.0%Michael Casey: 1.7%Boston.com: 0.6%Fundamental Attribution Error0.0%This article: 0.0%Michael Casey: 0.2%Boston.com: 0.0%Actor-Observer Bias0.0%This article: 0.0%Michael Casey: 0.2%Boston.com: 1.0%In-Group Bias0.0%This article: 0.0%Michael Casey: 0.2%Boston.com: 0.2%Out-Group Homogeneity Bias0.0%This article: 0.0%Michael Casey: 1.4%Boston.com: 2.7%Halo Effect0.0%This article: 0.0%Michael Casey: 0.0%Boston.com: 0.1%Horn Effect0.0%This article: 0.0%Michael Casey: 0.0%Boston.com: 0.0%Dunning-Kruger Effect0.0%This article: 4.7%Michael Casey: 1.3%Boston.com: 1.4%Recency Bias4.7%This article: 0.0%Michael Casey: 0.2%Boston.com: 0.4%Primacy Effect0.0%This article: 0.0%Michael Casey: 0.0%Boston.com: 0.0%Blind-Spot Bias0.0%This article: 0.0%Michael Casey: 2.0%Boston.com: 0.3%Ad Hominem0.0%This article: 0.0%Michael Casey: 1.2%Boston.com: 0.1%Straw Man0.0%This article: 10.3%Michael Casey: 1.6%Boston.com: 3.8%Appeal to Authority10.3%This article: 0.0%Michael Casey: 0.8%Boston.com: 1.1%False Dilemma0.0%This article: 0.0%Michael Casey: 1.4%Boston.com: 0.4%Slippery Slope0.0%This article: 0.0%Michael Casey: 0.3%Boston.com: 0.1%Circular Reasoning0.0%This article: 0.0%Michael Casey: 3.2%Boston.com: 3.1%Hasty Generalization0.0%This article: 0.0%Michael Casey: 0.3%Boston.com: 0.3%Red Herring0.0%This article: 7.1%Michael Casey: 0.2%Boston.com: 0.5%Bandwagon7.1%This article: 37.9%Michael Casey: 9.1%Boston.com: 6.2%Appeal to Emotion37.9%This article: 0.0%Michael Casey: 1.1%Boston.com: 0.5%Begging the Question0.0%This article: 0.0%Michael Casey: 2.6%Boston.com: 1.5%Post Hoc (False Cause)0.0%This article: 0.0%Michael Casey: 0.0%Boston.com: 0.2%Tu Quoque0.0%This article: 7.7%Michael Casey: 0.5%Boston.com: 0.4%Burden of Proof7.7%This article: 0.0%Michael Casey: 0.1%Boston.com: 0.1%Appeal to Nature0.0%This article: 0.0%Michael Casey: 0.5%Boston.com: 0.1%Composition/Division0.0%This article: 0.0%Michael Casey: 2.0%Boston.com: 2.2%Anecdotal0.0%This article: 0.0%Michael Casey: 0.1%Boston.com: 0.0%No True Scotsman0.0%This article: 5.3%Michael Casey: 2.0%Boston.com: 1.3%Ambiguity (Equivocation)5.3%This article: 0.0%Michael Casey: 0.0%Boston.com: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Michael Casey: 0.0%Boston.com: 0.1%Middle Ground0.0%This article: 0.0%Michael Casey: 0.0%Boston.com: 0.0%Personal Incredulity0.0%This article: 0.0%Michael Casey: 0.3%Boston.com: 0.0%Special Pleading0.0%This article: 0.0%Michael Casey: 0.0%Boston.com: 0.0%Genetic Fallacy0.0%This article: 0.0%Michael Casey: 1.2%Boston.com: 1.3%Unattributed Quote0.0%This article: 0.0%Michael Casey: 2.7%Boston.com: 1.6%Quote-first Misdirection0.0%This article: 0.0%Michael Casey: 4.5%Boston.com: 3.8%Biased Writer Voice0.0%This article: 0.0%Michael Casey: 2.8%Boston.com: 1.3%Indoctrination0.0%This article: 0.0%Michael Casey: 2.3%Boston.com: 0.3%Politically Left Leaning Bias0.0%This article: 0.0%Michael Casey: 0.2%Boston.com: 0.0%Politically Right Leaning Bias0.0%This article: 0.0%Michael Casey: 0.3%Boston.com: 2.1%Attempt to Sell a Product or S…0.0%

494 words analyzed.

Speakers

3speakers37%attributed speech311writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 15 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageIndira Talwani • 51 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageJennifer Davenport • 48 words • 0.0% coverageJennifer Davenport • 35 words • 0.0% coverageJennifer Davenport • 32 words • 0.0% coverageWriter's voice • 38 words • 0.0% coverageWriter's voice • 26 words • 0.0% coverageWriter's voice • 44 words • 0.0% coverageOffice of Management and Budget • 17 words • 0.0% coverage
Selected voice

Jennifer Davenport

100%flagged-word coverage
115 attributed words63% of attributed speech71% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

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.