classify-DLE.txt

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Given the following argument and definitions with their logical forms and examples, determine which of the fallacies defined below occurs in Premise 3 of the provided argument.
The argument may contain multiple fallacies. Only detect the most fitting fallacy within Premise 3.
Explain your decision and conclude with the applied fallacy in a separate line at the end as "Fallacy: <fallacy class>".

Fallacies:

Ambiguity:
Definition 1: When an unclear phrase with multiple definitions is used within the argument; therefore, does not support the conclusion.
Logical Form 1: Claim X is made. Y is concluded based on an ambiguous understanding of X.
Example 1: It is said that we have a good understanding of our universe.  Therefore, we know exactly how it began and exactly when.
Definition 2: When the same word (here used also for phrase) is used with two different meanings.
Logical Form 2: Term X is used to mean Y in the premise. Term X is used to mean Z in the conclusion.
Example 2: A feather is light. What is light cannot be dark. Therefore, a feather cannot be dark.

Impossible Expectations:
Definition 1: Comparing a realistic solution with an idealized one, and discounting or even dismissing the realistic solution as a result of comparing to a “perfect world” or impossible standard, ignoring the fact that improvements are often good enough reason.
Logical Form 1: X is what we have. Y is the perfect situation. Therefore, X is not good enough.
Example 1: Seat belts are a bad idea. People are still going to die in car crashes.

False Equivalence:
Definition 1: Assumes that two subjects that share a single trait are equivalent.
Logical Form 1: X and Y both share characteristic A. Therefore, X and Y are [behave] equal.
Example 1: They are both Felidae, mammals in the order Carnivora, therefore there's little difference between having a pet cat and a pet jaguar.

False Dilemma:
Definition 1: Presents only two alternatives, while there may be another alternative, another way of framing the situation, or both options may be simultaneously viable.
Logical Form 1: Either X or Y is true.
Example 1: I thought you were a good person, but you weren’t at church today.
Definition 2: Making the false assumption that when presented with an either/or possibility, that if one of the options is true that the other one must be false.
Logical Form 2: P or Q could be true. P is true. Therefore, Q is not true.
Example 2: Bill is 6’11” tall, thin, but muscular.  We know he either is a pro basketball player or a jockey.  We conclude that it is more probable that he is a pro basketball player than a pro basketball player or a jockey.

Biased Sample Fallacy:
Definition 1: Drawing a conclusion about a population based on a sample that is biased, or chosen in order to make it appear the population on average is different than it actually is.
Logical Form 1: Sample S, which is biased, is taken from population P. Conclusion C is drawn about population P based on S.
Example 1: Based on a survey of 1000 American homeowners, 99% of those surveyed have two or more automobiles worth on average $100,000 each.  Therefore, Americans are very wealthy.

Hasty Generalization:
Definition 1: Drawing a conclusion based on a small sample size, rather than looking at statistics that are much more in line with the typical or average situation.
Logical Form 1: Sample S is taken from population P. Sample S is a very small part of population P. Conclusion C is drawn from sample S and applied to population P.
Example 1: My father smoked four packs of cigarettes a day since age fourteen and lived until age sixty-nine.  Therefore, smoking really can’t be that bad for you.

Causal Oversimplification:
Definition 1: Post hoc ergo propter hoc - after this therefore because of this. Automatically attributes causality to a sequence or conjunction of events.
Logical Form 1: A is regularly associated with B; therefore, A causes B.
Example 1: Every time I go to sleep, the sun goes down.  Therefore, my going to sleep causes the sun to set.
Definition 2: Assumes there is a single, simple cause of an outcome.
Logical Form 2: X is a contributing factor to Y. X and Y are present. Therefore, to remove Y, remove X.
Example 2: Smoking has been empirically proven to cause lung cancer. Therefore, if we eradicate smoking, we will eradicate lung cancer.

Fallacy of Composition:
Definition 1: Inferring that something is true of the whole from the fact that it is true of some part of the whole.
Logical Form 1: A is part of B. A has property X. Therefore, B has property X.
Example 1: Hydrogen is not wet.  Oxygen is not wet.  Therefore, water (H2O) is not wet.
Definition 2: Inferring that something is true of one or more of the parts from the fact that it is true of the whole.
Logical Form 2:  A is part of B. B has property X. Therefore, A has property X.
Example 2:  His house is about half the size of most houses in the neighborhood. Therefore, his doors must all be about 3 1/2 feet high.

Fallacy of Exclusion:
Definition 1: When only select evidence is presented in order to persuade the audience to accept a position, and evidence that would go against the position is withheld.
Definition 2: Ignores relevant and significant evidence when inferring to a conclusion.
Logical Form 2: Evidence A and evidence B is available. Evidence A supports the claim of person 1. Evidence B supports the counterclaim of person 2. Therefore, person 1 presents only evidence A.
Example 2: Hydrogen is not wet.  Oxygen is not wet.  Therefore, water (H2O) is not wet.
Definition 3: Discarding the relevance of Premise 2 within the argument.
Logical Form 3: Evidence A and evidence B is available. Evidence A supports the claim of person 1. Evidence B supports the counterclaim of person 2. Therefore, evidence B is irrelevant to the claim.
Example 3:  His house is about half the size of most houses in the neighborhood. Therefore, his doors must all be about 3 1/2 feet high.

Argument:
Premise 1: "@@p0@@"
Premise 2: "@@context@@"
Premise 3: "@@fallacious_premise@@"
Therefore: "@@claim@@"