Dicto Simpliciter

"Jumping to Conclusions" or "Hasty Generalization"

Generally, this fallacy occurs when too few examples are used to prove a point about all (or even most) members of a class or category.

The examples observed may be factual, but there are not enough of them to warrant a conclusion. 

This logical fallacy should not be confused with a false/faulty extrapolation, which is a hasty generalization that involves a prediction. The standard Dicto Simpliciter does not involve a prediction.

There are at least two sub-categories of the fallacy

The Fallacy of Accident

This fallacy occurs when a generalization is made about a seemingly sensible rule, but this sensible rule doesn't work well in all situations. 

There are occasional exceptions to some generally agreed-upon rules?

Examples: 


Stealing is bad.

What about stealing to feed your starving children?

What about stealing a pack of cigarettes from someone to prevent them from smoking and getting cancer?


One should always return borrowed items when the person who loaned them wants them back.

What if the neighbor who loaned you his shotgun just said, "I'm going to kill my wife" before politely asking, "Can I have my 12-gauge back now?"


Never talk to strangers.

I guess nobody can make new friends and everyone will have to just be single for the rest of their lives, right?

What if I'm hiking on a distant mountain trail when I slip, fall, and badly break my leg. Should I talk to the stranger hiking past or keep quiet and probably die from exposure?

Faulty or Misleading Statistic

Statistics can be misleading for a number of reasons. They could be derived from an insufficient sample size (related to stereotyping), but they could also be taken from irrelevant sample populations that have nothing to do with what is being represented. Also, they could be misleading because of the ways in which the numbers are presented.

Not all statistics are created equal. Being critical of them is important.

Whenever statistics are presented, ask:



"A Word on Statistics"

Poem by Wislaw Szymborska, Translated by Joanna Trzeciak

Example: 

"Each time I see an American TV show, the people wear their shoes inside their houses; therefore, all Americans wear their shoes inside their houses."

This is obviously an unfair stereotyping based on only a handful of irrelevant examples. Television shows aren't going to sacrifice precious plot time to show people taking off their shoes. Most Americans, in fact, do take of their shoes upon entering their houses.

This fallacy is often used to explain prejudice, and is usually perpetrated by people who have limited experience with those who they are prejudiced against. They use dicto simpliciters to fallaciously justify their prejudices because it feels logical.

Example: Mr. Spagnolo threw out his back while reaching down to click the mouse on his computer; therefore, reaching to clicking a mouse on a computer is an extremely dangerous activity.

While the unfortunate back-throwing-out incident is true 😵, it is only one incident and could be attributed to 1,000 other factors (namely the huge bench-pressing and squat session he completed five minutes before deciding to check his email). 🤣 He worked in a factory for five years before becoming a teacher, which didn't do his back any favors. Also, he has bad posture and sits on his couch a lot.

Honestly, this is an over-generalization and the inherent dangers of mouse-clicking cannot be determined from a sample size of only one incident.

People sometimes throw out their backs by sneezing (no joke!). Does this mean that sneezing is dangerous? No.

Example: 

An article titled: "Hidden Camera Proves the True Nature of Pit Bulls. Must See" was accompanied by this video.

An accurate title that doesn't mislead would actually be: "Camera Shows A Cute Connection between Pit Bull and Owner."

The video to the right doesn't show "the true nature of pit bulls" any more than THIS VIDEO shows the true nature of all cats or THIS NEWS story shows the true nature of all people from New Zealand.

"ALL" is a very dangerous word in debate. Avoid absolutes unless you are 100% sure of their accuracy.

Example:

This Fox "News" representation of Obamacare Enrollment isn't exactly a misleading statistic. At the time of airing, the numerical statistics shown here were actually accurate. 

The misleading part occurs with the visual representation of the statistics. The size of the bars in the chart give a very different impression of what the statistics actually mean.

On a side note, the Affordable Care Act ("Obamacare") did surpass its enrollment goal.