BS Summary: This article contains 21 faulty reasoning types, including Appeal to Authority, Anecdotal, and Pessimism Bias, with Negativity Bias as the most egregious example at 21.9% saturation with 172 hits. Analysis detected 1,186 faulty-reasoning hits from 784 analyzed words, generating a BS Score of 39.9% and a BS Rank of 42% (15,564 of 26,447 articles). This article is better (less manipulative) than 58.80% of the article peer group.

How To Tell If an Endangered Giant Manta Is Pregnant: Give Her an Ultrasound (Maria) 
The author writes , “Giant manta rays are otherworldly leviathans gliding through the world’s seas on massive wings. 
But even though they are the world’s largest ray species, a fundamental part of their lives is obscured: where they give birth. 
 Now, a team of scientists in Mexico has reported the first use of underwater ultrasound scans to detect pregnancies in these animals, a strategy that may help provide answers. 
An endangered species, giant oceanic mantas are sparsely distributed and travel vast distances, making their reproduction difficult to study.” 
Trump Administration Demands Hospitals Share Emergency Room Records (Dana) 
The authors write , “A tiny federal agency tasked with protecting the public from injuries caused by lawn mowers and coffeemakers is demanding that some of the nation’s biggest health systems turn over detailed, personally identifiable medical records of all patients who seek help at their emergency rooms. 
The Consumer Product Safety Commission, responsible for tracking and issuing recalls of dangerous products sold in the U.S., began discreetly pressuring hospital executives this year to share personally identifiable health data with a private contractor. 
But hospital lawyers and other industry experts have questioned the agency’s authority to collect, its ability to safeguard such a swath of sensitive information, and whether it has followed the legal process to overhaul its surveillance system.” 
‘Every Time the Rain Falls, the Fear Comes Back’: Life in Lagos Under the Constant Threat of Floods (Laura) 
From The Guardian : “Murky water first tore down a perimeter fence, then bubbled into the yard before spilling into every room. 
Within minutes, electronics, kitchen appliances, furniture, documents and academic certificates lay submerged. 
With the water rising rapidly, Daniel Ebiesua evacuated his home in the Shogunle area of Lagos, with his wife, their two-week-old baby, four-year-old son and his mother-in-law to a neighbour’s upstairs apartment. 
There they stayed trapped for four hours, helplessly watching the flood swallow the streets below. 
 As Nigeria sees more frequent and devastating floods caused by torrential rain combined with clogged drainage channels and rising sea levels, experts say the rebuilding process does not start when the waters recede, especially with mounting anxiety, grief and psychological fatigue.” 
After Refusing a $287 Repair Bill, Portland Renter Beats His Landlord in Court, Wins $32K Verdict (Reader Steve) 
From The Oregonian : “A few days before trial, Jonah Spring had a decision to make: Drop his lawsuit against his former landlord or proceed, knowing that if he lost he could be on the hook for his landlord’s legal costs, which could soar into the six figures. 
A lawyer for the landlord made clear under no uncertain terms that the Portland renter was about to make a stupid mistake  intimating in an email to Spring’s attorneys that Spring ‘probably has a lower IQ.’ 
Lawyer John Berman also said he would cause Spring ‘great harm’ and use Spring’s words to ‘absolutely destroy’ him on the stand.” 
Measles Is Becoming So Common That Treatments May Soon Be Needed (Sean) 
From Wired : “Up until recently, measles vaccination has been so effective that there’s been little medical or financial incentive to develop treatments for the disease. 
But as measles cases hit a 35-year high and vaccination rates continue to decline in the US, a handful of biotech companies and academic groups have started working on measles treatments for those infected with the virus as well as vulnerable individuals needing short-term protection. 
It will likely be years, however, before these countermeasures are available, and it’s even more uncertain if those who refuse vaccines would take such treatments.” 
Giant Fire Tornadoes Could Clean Up Oil Spills Faster With Less Pollution (Mili) 
The author writes , “When a major oil spill occurs at sea, emergency crews often face a difficult choice. 
They can allow the oil to spread across the water, threatening coastlines and marine life, or they can set it on fire. 
Burning the oil, a technique known as an in situ burn, can prevent the slick from expanding. 
However, it also produces thick clouds of black smoke, releases soot into the atmosphere, and leaves behind a layer of unburned residue floating on the ocean’s surface. 
Now, researchers have demonstrated a striking new approach that could make this process far more effective. 
In a first-of-its-kind large-scale study, scientists created giant fire whirls, spinning columns of flame that resemble fire tornadoes, and found they burn oil faster and more cleanly than conventional methods.” 
How To Tell If an Endangered Giant Manta Is Pregnant: Give Her an Ultrasound originally appeared on WhoWhatWhy 
Article reasoning-pattern comparisonThis article: 4.5%Whowhatwhy Editors: 1.9%WhoWhatWhy: 6.2%Confirmation Bias4.5%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.6%Anchoring Bias0.0%This article: 4.5%Whowhatwhy Editors: 1.8%WhoWhatWhy: 2.6%Availability Heuristic4.5%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.9%Representativeness Heuristic0.0%This article: 0.0%Whowhatwhy Editors: 0.4%WhoWhatWhy: 1.4%Hindsight Bias0.0%This article: 3.8%Whowhatwhy Editors: 0.7%WhoWhatWhy: 1.1%Overconfidence Bias3.8%This article: 7.9%Whowhatwhy Editors: 5.5%WhoWhatWhy: 4.4%Framing Effect7.9%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.3%Loss Aversion0.0%This article: 3.3%Whowhatwhy Editors: 0.5%WhoWhatWhy: 0.5%Status Quo Bias3.3%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.3%Sunk Cost Effect0.0%This article: 5.5%Whowhatwhy Editors: 3.6%WhoWhatWhy: 2.3%Optimism Bias5.5%This article: 11.0%Whowhatwhy Editors: 3.0%WhoWhatWhy: 2.9%Pessimism Bias11.0%This article: 21.9%Whowhatwhy Editors: 11.8%WhoWhatWhy: 13.9%Negativity Bias21.9%This article: 0.0%Whowhatwhy Editors: 0.1%WhoWhatWhy: 1.3%Self-Serving Bias0.0%This article: 4.7%Whowhatwhy Editors: 1.0%WhoWhatWhy: 2.3%Fundamental Attribution Error4.7%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.0%Actor-Observer Bias0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 1.6%In-Group Bias0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 1.4%Out-Group Homogeneity Bias0.0%This article: 2.3%Whowhatwhy Editors: 0.8%WhoWhatWhy: 0.5%Halo Effect2.3%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.5%Horn Effect0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.0%Dunning-Kruger Effect0.0%This article: 2.3%Whowhatwhy Editors: 0.8%WhoWhatWhy: 0.8%Recency Bias2.3%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.3%Primacy Effect0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.0%Blind-Spot Bias0.0%This article: 7.5%Whowhatwhy Editors: 1.9%WhoWhatWhy: 5.2%Ad Hominem7.5%This article: 0.0%Whowhatwhy Editors: 0.6%WhoWhatWhy: 0.7%Straw Man0.0%This article: 18.8%Whowhatwhy Editors: 3.8%WhoWhatWhy: 2.7%Appeal to Authority18.8%This article: 5.2%Whowhatwhy Editors: 1.4%WhoWhatWhy: 2.2%False Dilemma5.2%This article: 0.0%Whowhatwhy Editors: 0.8%WhoWhatWhy: 2.1%Slippery Slope0.0%This article: 0.0%Whowhatwhy Editors: 0.3%WhoWhatWhy: 0.2%Circular Reasoning0.0%This article: 0.0%Whowhatwhy Editors: 3.4%WhoWhatWhy: 9.6%Hasty Generalization0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.2%Red Herring0.0%This article: 5.7%Whowhatwhy Editors: 0.7%WhoWhatWhy: 0.7%Bandwagon5.7%This article: 5.9%Whowhatwhy Editors: 5.7%WhoWhatWhy: 6.0%Appeal to Emotion5.9%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 1.3%Begging the Question0.0%This article: 0.0%Whowhatwhy Editors: 1.0%WhoWhatWhy: 1.6%Post Hoc (False Cause)0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.1%Tu Quoque0.0%This article: 0.0%Whowhatwhy Editors: 0.7%WhoWhatWhy: 1.0%Burden of Proof0.0%This article: 0.0%Whowhatwhy Editors: 1.0%WhoWhatWhy: 0.2%Appeal to Nature0.0%This article: 0.0%Whowhatwhy Editors: 0.2%WhoWhatWhy: 0.2%Composition/Division0.0%This article: 13.0%Whowhatwhy Editors: 2.1%WhoWhatWhy: 3.0%Anecdotal13.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.2%No True Scotsman0.0%This article: 4.5%Whowhatwhy Editors: 1.1%WhoWhatWhy: 0.7%Ambiguity (Equivocation)4.5%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.2%Middle Ground0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.3%Personal Incredulity0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.4%Special Pleading0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.1%Genetic Fallacy0.0%This article: 6.1%Whowhatwhy Editors: 7.0%WhoWhatWhy: 2.4%Unattributed Quote6.1%This article: 6.1%Whowhatwhy Editors: 2.2%WhoWhatWhy: 1.0%Quote-first Misdirection6.1%This article: 6.8%Whowhatwhy Editors: 5.6%WhoWhatWhy: 17.1%Biased Writer Voice6.8%This article: 0.0%Whowhatwhy Editors: 0.2%WhoWhatWhy: 2.8%Indoctrination0.0%This article: 0.0%Whowhatwhy Editors: 4.0%WhoWhatWhy: 9.5%Politically Left Leaning Bias0.0%This article: 0.0%Whowhatwhy Editors: 0.0%WhoWhatWhy: 0.2%Politically Right Leaning Bias0.0%This article: 0.0%Whowhatwhy Editors: 0.1%WhoWhatWhy: 0.6%Attempt to Sell a Product or S…0.0%

784 words analyzed.

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Analysis

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