BS Summary: This article contains 2 faulty reasoning types, including Optimism Bias, with Halo Effect as the most egregious example at 5.4% saturation with 25 hits. Analysis detected 45 faulty-reasoning hits from 463 analyzed words, generating a BS Score of 5% and a BS Rank of 1% (21,739 of 21,887 articles). This article is better (less manipulative) than 99.30% of the article peer group.

The Detroit Department of Construction and Demolition gave city council an update on the removal of the contaminated dirt in the city on Monday. 
The Department has replaced tainted backfill in more than 100 properties. 
That’s out of the 450 lots that were identified. 
The average cost of the fill removal and replacement is about $36,000 per site. 
Department Director Tim Palazzo says they have tightened up process for approving construction fill materials over the last several months. 
“The first thing is that we collapsed the number of sites and sources from which we receive fill material down to seven public pits. 
These only excavate native sand, gravel, soil from longstanding operations.” 
Palazzo says they inspect those sites on a monthly basis and send their staff—as well as a third-party environmental consultant—to oversee operations at the sites. 
He says they have also started sampling the fill before it even leaves the source site. 
-Reporting by Bre’Anna Tinsley 
Additional headlines for Tuesday, July 21, 2026 
Community discussion about ICE 
The Southfield Neighbors Action Committee is hosting a community discussion Wednesday about ICE enforcement in Southfield. 
“What Does It Mean To Be A Good Neighbor When ICE Moves In?” 
will be moderated by Kermit Williams, political director of Oakland Forward. 
Panelists include Elida Reyes from Community Action for Empowerment, Lauren Fink from Southfield Neighbors Action Committee, Dr. 
Patricia Talley from Mexico Negro and U.S. 
House Representative Rashida Tlaib. 
The event is Wednesday from 6:30- 9 p.m. in Room 115 at the Southfield Pavilion at 26000 Evergreen Road. 
Good Food for Michigan 
Dearborn Public Schools has received a state grant designed to bring more Michigan-grown food to its cafeterias. 
The Good Food for Michigan Project is giving the district more than $460,000. 
Dearborn schools serve more than 3 million meals to around 20,000 students at more than 30 sites. 
The Good Food for Michigan Project is a collaboration between the Michigan Department of Agriculture & Rural Development, the Center for Good Food Purchasing, and the Michigan State University Center for Regional Food Systems. 
Detroit Riverfront hosts art exhibit 
People visiting Detroit’s Riverfront and Southwest Greenway can now take in a little bit of the DIA’s art collection. 
The Detroit Riverfront Conservancy is hosting the museum’s Inside Out project featuring large-scale reproductions of 7 works. 
The pieces will be in place until October. 
The Hamtramck Parks Conservancy and the city’s recreation department are partnering to offer a girls soccer clinic on August 17 . 
Women coaches and trainers will work with girls between the ages of 10 and 17 years old. 
Balls, nets and pennies are provided. 
The clinic runs from 9:30-11:30 a.m. at the Veterans Park Soccer Arena at 8684 Joseph Campau. 
Article reasoning-pattern comparisonThis article: 0.0%Sascha Raiyn: 0.6%WDET: 1.7%Confirmation Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.4%Anchoring Bias0.0%This article: 0.0%Sascha Raiyn: 0.9%WDET: 2.3%Availability Heuristic0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.7%Representativeness Heuristic0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.2%Hindsight Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 1.0%Overconfidence Bias0.0%This article: 0.0%Sascha Raiyn: 4.6%WDET: 4.7%Framing Effect0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.9%Loss Aversion0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.3%Status Quo Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Sunk Cost Effect0.0%This article: 4.3%Sascha Raiyn: 1.3%WDET: 3.5%Optimism Bias4.3%This article: 0.0%Sascha Raiyn: 2.7%WDET: 0.9%Pessimism Bias0.0%This article: 0.0%Sascha Raiyn: 2.2%WDET: 3.4%Negativity Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 1.6%Self-Serving Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.2%Fundamental Attribution Error0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Actor-Observer Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 1.2%In-Group Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.6%Out-Group Homogeneity Bias0.0%This article: 5.4%Sascha Raiyn: 4.4%WDET: 5.6%Halo Effect5.4%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.0%Horn Effect0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.0%Dunning-Kruger Effect0.0%This article: 0.0%Sascha Raiyn: 0.6%WDET: 0.9%Recency Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.3%Primacy Effect0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.0%Blind-Spot Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.2%Ad Hominem0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Straw Man0.0%This article: 0.0%Sascha Raiyn: 0.5%WDET: 3.3%Appeal to Authority0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 1.0%False Dilemma0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.0%Slippery Slope0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Circular Reasoning0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 3.4%Hasty Generalization0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Red Herring0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.5%Bandwagon0.0%This article: 0.0%Sascha Raiyn: 4.1%WDET: 4.6%Appeal to Emotion0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.6%Begging the Question0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 1.5%Post Hoc (False Cause)0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.0%Tu Quoque0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.4%Burden of Proof0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Appeal to Nature0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Composition/Division0.0%This article: 0.0%Sascha Raiyn: 1.4%WDET: 1.8%Anecdotal0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%No True Scotsman0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 1.2%Ambiguity (Equivocation)0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Middle Ground0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Personal Incredulity0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Special Pleading0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.0%Genetic Fallacy0.0%This article: 0.0%Sascha Raiyn: 0.4%WDET: 0.8%Unattributed Quote0.0%This article: 0.0%Sascha Raiyn: 1.4%WDET: 0.7%Quote-first Misdirection0.0%This article: 0.0%Sascha Raiyn: 2.0%WDET: 4.1%Biased Writer Voice0.0%This article: 0.0%Sascha Raiyn: 0.8%WDET: 2.6%Indoctrination0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.3%Politically Left Leaning Bias0.0%This article: 0.0%Sascha Raiyn: 0.0%WDET: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Sascha Raiyn: 9.2%WDET: 7.1%Attempt to Sell a Product or S…0.0%

463 words analyzed.

Speakers

1speaker21%attributed speech368writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 14 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageTim Palazzo • 20 words • 0.0% coverageTim Palazzo • 24 words • 0.0% coverageTim Palazzo • 10 words • 0.0% coverageTim Palazzo • 25 words • 0.0% coverageTim Palazzo • 16 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 34 words • 0.0% coverageWriter's voice • 5 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 6 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverage
Selected voice

Tim Palazzo

47%flagged-word coverage
95 attributed words100% of attributed speech0% 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.