when a person sharpens thier fingernail and proceeds to violently finger a girl. Can be performed girl on girl or heterosexually.
by Perri O'key May 10, 2010
possibly the coolest wrestler from wwf. accompanied by his friendly toothpick he wrecked havoc throughout the 90's.
by jd December 9, 2003
Philosophical statement based on Occam's Razor.
"I like boobies (major premise)
Girls have boobies (minor premise)
I like girls with boobies (conclusion)"
"I like boobies (major premise)
Girls have boobies (minor premise)
I like girls with boobies (conclusion)"
by K-Noodle October 30, 2006
A variation on Occam's Razor devised by Hank Green theorizing that if an anomaly in society can be explained by socioeconomic status, it's probably that, rather than whatever obscure detail the anomaly is trying to measure.
Does playing racquet sports make people who play them live longer than everyone else? No, Hank's Razor indicates that people who play racquet sports are more likely to be wealthy and have better access to health care.
by Zijayar July 19, 2023
Piracy Group, Founded in 1985.
(1911 is 777 in the Hexadecimal number system (Base 16). 777 Is the opposite to 666.)
(1911 is 777 in the Hexadecimal number system (Base 16). 777 Is the opposite to 666.)
by aNthraXx January 16, 2004
Occam's razor is a logical principle attributed to the mediaeval philosopher William of Occam (or Ockham). The principle states that one should not make more assumptions than the minimum needed. This principle is often called the principle of parsimony. It underlies all scientific modelling and theory building. It admonishes us to choose from a set of otherwise equivalent models of a given phenomenon the simplest one. In any given model, Occam's razor helps us to "shave off" those concepts, variables or constructs that are not really needed to explain the phenomenon. By doing that, developing the model will become much easier, and there is less chance of introducing inconsistencies, ambiguities and redundancies.
Though the principle may seem rather trivial, it is essential for model building because of what is known as the "underdetermination of theories by data". For a given set of observations or data, there is always an infinite number of possible models explaining those same data. This is because a model normally represents an infinite number of possible cases, of which the observed cases are only a finite subset. The non-observed cases are inferred by postulating general rules covering both actual and potential observations.
For example, through two data points in a diagram you can always draw a straight line, and induce that all further observations will lie on that line. However, you could also draw an infinite variety of the most complicated curves passing through those same two points, and these curves would fit the empirical data just as well. Only Occam's razor would in this case guide you in choosing the "straight" (i.e. linear) relation as best candidate model. A similar reasoning can be made for n data points lying in any kind of distribution.
Occam's razor is especially important for universal models such as the ones developed in General Systems Theory, mathematics or philosophy, because there the subject domain is of an unlimited complexity. If one starts with too complicated foundations for a theory that potentially encompasses the universe, the chances of getting any manageable model are very slim indeed. Moreover, the principle is sometimes the only remaining guideline when entering domains of such a high level of abstraction that no concrete tests or observations can decide between rival models. In mathematical modelling of systems, the principle can be made more concrete in the form of the principle of uncertainty maximization: from your data, induce that model which minimizes the number of additional assumptions.
This principle is part of epistemology, and can be motivated by the requirement of maximal simplicity of cognitive models. However, its significance might be extended to metaphysics if it is interpreted as saying that simpler models are more likely to be correct than complex ones, in other words, that "nature" prefers simplicity.
Though the principle may seem rather trivial, it is essential for model building because of what is known as the "underdetermination of theories by data". For a given set of observations or data, there is always an infinite number of possible models explaining those same data. This is because a model normally represents an infinite number of possible cases, of which the observed cases are only a finite subset. The non-observed cases are inferred by postulating general rules covering both actual and potential observations.
For example, through two data points in a diagram you can always draw a straight line, and induce that all further observations will lie on that line. However, you could also draw an infinite variety of the most complicated curves passing through those same two points, and these curves would fit the empirical data just as well. Only Occam's razor would in this case guide you in choosing the "straight" (i.e. linear) relation as best candidate model. A similar reasoning can be made for n data points lying in any kind of distribution.
Occam's razor is especially important for universal models such as the ones developed in General Systems Theory, mathematics or philosophy, because there the subject domain is of an unlimited complexity. If one starts with too complicated foundations for a theory that potentially encompasses the universe, the chances of getting any manageable model are very slim indeed. Moreover, the principle is sometimes the only remaining guideline when entering domains of such a high level of abstraction that no concrete tests or observations can decide between rival models. In mathematical modelling of systems, the principle can be made more concrete in the form of the principle of uncertainty maximization: from your data, induce that model which minimizes the number of additional assumptions.
This principle is part of epistemology, and can be motivated by the requirement of maximal simplicity of cognitive models. However, its significance might be extended to metaphysics if it is interpreted as saying that simpler models are more likely to be correct than complex ones, in other words, that "nature" prefers simplicity.
One should not increase, beyond what is necessary, the number of entities required to explain anything
by onomiyaki June 29, 2005
Kermit's Razor
Named after Kermit the frog who was of course married to Miss Piggy, the principle of Kermit's Razor goes something like: If there are two girls in a dating app bio photo, it usually belongs to the fatter of the two.
Named after Kermit the frog who was of course married to Miss Piggy, the principle of Kermit's Razor goes something like: If there are two girls in a dating app bio photo, it usually belongs to the fatter of the two.
Person 1: "There's two chicks in the tinder bio photos. I can't tell who the profile belongs to."
Person 2: "Kermit's Razor. Odds are it belongs to the larger of the two women."
Person 2: "Kermit's Razor. Odds are it belongs to the larger of the two women."
by Jerzy Radocovid December 12, 2022