PHIL 210

Winter 2019

Outline

• Outline

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0. Final

1. Self-test
2. DB activities
3. Quizzes
4. Glossary

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1. Deductive Argument

1.0 Glossary terms

• Antecedent
• Assertion
• Conjunctive statement (conjunction)
• Consequent
• Denying the antecedent
• Disjunctive statement (disjunction)
• Disjunctive syllogism
• Inference
• Soundness
• Validity

1.1 Self-Test

1. "If taxes are cut, social programs will be cut. There will be cuts to social programs. So, taxes will be cut." This argument is an example of:
   • Affirming the consequent
2. "If taxes are cut, social programs will be cut. There will be cuts to social programs. So, taxes will be cut." This argument is valid.
   • False
3. "Either Obama is a republican or he is a democrat. He is not a republican. So he must be a democrat." This argument is in the form of:
   • Disjunctive syllogism
4. "Either Obama is a republican or he is a democrat. He is not a republican. So he must be a democrat." This argument is:
   • Sound and valid
5. Having true premises is necessary for being valid.
   • False
6. Having true premises is sufficient for being sound.
   • False
7. If an argument is sound, it necessarily has a true conclusion.
   • True
8. The truth of the conjunction "Jane is a lawyer and lives in New Jersey" is sufficient for the truth of the disjunction "Jane is a lawyer or lives in New Jersey".
   • True
9. "Dave takes the bus to work when it rains. Because before, when he would try to walk, he would always end up getting soaked when a car would drive too fast through a puddle." Is this an argument or an explanation?
   • Explanation: Here the person saying this would not be trying to convince you that Dave walks to work, but rather explain why Dave walks to work.
10. "Obama will win the next election. Since he will only lose if he is very unpopular. But he will be unpopular only if the economy is in awful shape, and by the time of the next election we will have recovered from the recession." Is this an argument or an explanation?
    • Argument: An explanation assumes that something is true and tries to say why it is true. An argument gives you reasons why you should believe that something is true.

1.2 Statement, Assertion, Proposition

• Statement: A statement(assertion, proposition, claim) is anything that can either be true or false.
  • “Dave is tall.”
  • “Dave should stay in school.

1.3 Argument

• Definition: An argument is a series of statements(premises) that are intended to lend support to a conclusion.
• Validity: An argument is valid if it is not possible for the premises to all be true and the conclusion false.
• Soundness: An argument is sound if it meets two conditions:
  1. It is valid.
  2. All of its premises are true.
• Note on Terminology
  • Validity and soundness apply to arguments (not to assertions).
  • Truth and falsehood apply to assertions (not to arguments).
  • Premises imply a conclusion.
  • People infer a statement.

1.4 Logical

• Law of Identity
  • $P$ if and only if $P$.
• Law of Non-Contradiction
  • Not both $P$ and $\text{not-}P$
• Law of Excluded Middle
  • Either $P$ or $\text{not-}P$

1.5 Disjunctive Argument Forms

• Disjunctive syllogism
  1. $P$ or $Q$
  2. Not $Q$
  3. Therefore, $P$
• Constructive dilemma
  1. $P$ or $Q$
  2. If $P$ then $R$
  3. If $Q$ then $S$
  4. Therefore, $R$ or $S$
• Basic conditional
  • If $P$ then $Q$.
  • $P$ is the antecedent
  • $Q$ is the consequent.

1.6 Conditional Forms

• Valide Conditional Forms
  • Modus ponens
    1. If $P$ then $Q$
    2. $P$
    3. Therefore, $Q$
  • Modus tollens
    1. If $P$ then $Q$
    2. Not $Q$
    3. Therefore, not $P$
• Invalid Conditional Forms
  • Denying the antecedent
  • Affirming the consequent
• Necessary and Sufficient Conditions
  • To say $A$ is necessary for $B$ is to say you cannot have $B$ without $A$.
  • If $A$ is necessary for $B$, then $B$ is sufficient for $A$.

1.7 Assertion, Definition, Argument or Explanation

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2. Evidence Adds up

2.0 Glossary Terms

• Ampliative argument
• Analogy
• Cogency
• Defeasibility
• Inductive argument
• Mill's methods

2.1 Self-test

1. A cogent argument is:
   • Neither sound nor valid
2. A cogent argument cannot lead from true premises to a false conclusion.
   • False
3. "Every winter for which we have data, there has been less than 400 cm of snow falling in Montreal. So this year we should expect less than 400 cm as well." This is an example of:
   • Inductive reasoning
4. What are some types of arguments that can be undermined without discovering that any of the premises are false?
   • Inductive, abductive and argument from analogy: All non-deductively valid arguments can be undermined without discovering the falsity of one of the premises.
5. In a hospital, there is an outbreak of a set of strange new symptoms. A researcher discovers that everyone who had the symptoms had been treated by some doctor who had recently come from the morgue. The researcher concludes that something about the morgue is causing the symptoms. Which of Mill's methods is being used here?
   • Method of agreement: The causal conclusion is based on a similarity between all of the cases.
6. Researchers discovered that IQ scores in children are related to the level of manganese in drinking water. The higher the levels of manganese, the lower the IQ scores in the children tested. These researchers are using which of Mill's methods?
   • Method of co-variation: The more of something that is found, the stronger the effect.
7. Alice goes out at 11 a.m. to mow her lawn. The street and sidewalk are dry, but the lawn is quite wet. She concludes that it must have rained during the night, but stopped early enough that the sun could dry up the paved areas. What kind of reasoning is Alice using here?
   • Abductive

2.2 Ampliative Arguments

• Deductive Reasoning
  • In deductive reasoning, the conclusion is contained in premises.
  • In a deductively valid argument, the truth of the premises is sufficient for the truth of the conclusion.
• Ampliative Arguments
  • Arguments that go beyond what is deductively implied by the premises are called ampliative arguments.

2.3 Cogent Arguments

• Definition: Invalid arguments but give some good reasons for believing a claim.
• Whereas validity is an absolute notion, cogency is a matter of degree.

2.4 Inductive Reasoning

• Inductive reasoning is a type of ampliative reasoning of the form
  • All cases of type A so far have had feature B, so a new case of type A will also have feature B.
• State of Information
  • A belief is credible if your total state of information counts as reason to believe it.
• Defeasibility
  • For almost anything we believe it is possible that new evidence would make it unreasonable to continue to believe it.

2.5 Abduction

• Abduction is reasoning to the best explanation. If some claim, if true, explains a lot of what we already know, then that is good reason for accepting the new claim.

2.6 Analogy

• Arguments from analogy are very common.
• When evaluating an argument from analogy, the important question to ask is whether there is an important disanalogy between the two cases.
• That is, is there a relevant difference between the two cases that blocks the intended conclusion from following?

2.7 Mill’s Methods

• Method of agreement:
  • If there is only one factor F in common between two situations in which effect E is observed, then it is reasonable to believe that F causes E.
• Method of difference:
  • If E is observed in situation S1, but not in S2, and the only relevant difference between them is that S1 has factor F and S2 does not, then it is reasonable to believe that F causes E.
• Joint method of agreement and disagreement:
  • If in a range of situations E is observed when and only when F is present, then it is reasonable to believe that F causes E.
• Method of co-variation:
  • If the degree to which E is observed is proportional to the amount of F present, then it is reasonable to conclude that F is causally related to E. (We cannot be sure is F causes E, E causes F or there is a common cause for both of them.)
• Methods of residues (this applies to cases where we cannot isolate F all on its own):
  • If we know that G causes D (but not E), and in all cases where we see G and F we see both E and D, then we can conclude that F likely causes E.

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3. Language, Non Language and Argument

3.0 Glossary Terms

• Burden of proof
• Enthymemes
• False presuppositions
• Lexical ambiguity
• Misquote
• Naturalistic fallacy
• Polysemy
• Universal quantifiers
• Rhetoric
• Sorites reasoning
• Weasel word

3.1 Self-test

1. Rhetorical questions are usually used for stylistic purposes, but they can also be used to shift the burden of proof.
   • True
2. The sentence "Steve became somewhat angry"
   • Has a weasel word as a qualifier
3. The sorites paradox shows that vague terms are hopelessly unclear and are best avoided.
   • False
4. "A human fetus is just that: human. It is not a panda, giraffe or polar bear fetus. As a human, it has an obvious right to life." This passage contains:
   • An equivocation: "Human" has two meanings.
5. "Alice is either in her office or at the library. So she must be at the library." This argument:
   • Is an enthymeme: This argument is invalid as it stands, but clearly has an implicit premise. The speaker here is taking it for granted that Alice is not in her office.
6. If an article presents an uninterrupted direct quotation, then you can be sure that that is what was actually said.
   • False: It could always be a misattribution (someone else said the same thing), or simply a lie.
7. "Rich people, as a group, have more education than the poor. They perform jobs requiring more training and skill. They also have had the chance to develop an appreciation for the finer things in life. So the economic inequalities are justified." This is an example of:
   • The naturalistic fallacy

3.2 Rhetorical Questions

• Sometimes arguments contain a premise that is in the form of a question.
• For example: 
  • Do you care about your child’s health? 
  • If you cared about your child’s health, 
  • you would not let them eat at McDonald’s. 
  • So don’t bring your children to McDonald’s.
• The person putting forward this argument is not wondering whether parents care about the health of their children. Here the rhetorical question is just a stylistic variant of the assertion “You care about the health of your children”.

3.2 Burden of Proof

• Presuppositions: When we say some things, we can often presuppose many others.
  • Have you stopped beating your wife?
• Rhetorical Questions
  • If someone tells you that you should buy a Mazda, you would expect them to be able to justify their claim.
  • If someone says: “Why not buy a Mazda?”, they are suggesting that you should buy one. But now the speaker is not committed to justifying the claim that you should buy one. The speaker has placed the burden of proof on you to disprove the claim that you should buy a Mazda.

3.2 Quantifiers, Qualifiers and Weasel Words

• Quantifiers: Quantifiers like “many”, “lots” and “some” can likewise make the truth conditions unclear.
  • Some of the hundred new law students are women.
  • By our ordinary standards, this is true if at least two or three are, and not all of them are.
  • But things are not so clear.
  • It would be at the very least misleading to say this if 98 of the new law students were women.
  • Do lots of children like beets? That depends on what counts as lots.
• Qualifiers
  • Dave is a good driver. 
  • Dave is a fairly good driver.
• Weasel word
  • The qualifier “fairly” here is a weasel word.
  • The first sentence is clearly false if Dave has one accident every year (where he is at least partially at fault).
  • It is unclear what the truth conditions of the second sentence are. One might think it is true even in the case just described.

3.3 Sorites Paradox

• Everything is vague to a degree you do not realize till you have tried to make it precise.

3.4 Ambiguity

• While vagueness involves the problem of drawing sharp boundaries for a concept, ambiguity arises when a written or spoken sentence can be given two (or possibly more) distinct interpretations.
• Syntactic ambiguity: The ambiguity arises due to the (poor) construction of the sentence.
  • The boy was standing in front of the statue of George Washington with his sister.
• Lexical ambiguity: when a string of spoken sounds or written letters have more than one possible meaning.
  • Dave took his pale green coat because it was lighter. 
• Homonymy vs. Polysemy
  • If lexical ambiguity involves two meanings that are not closely related, it is called homonymy.
  • When the two meanings are closely related, it is known as polysemy. Polysemous uses can often set upequivocations.
  • An equivocation is a fallacy which plays on an ambiguity.

3.5 Quotation and Misquotation

• Sometimes a quote is interrupted merely to save space. But a quote pasted together from several sections of a piece is a red flag. It often indicates that no uninterrupted quote that conveys the same meaning could be found.

3.6 Enthymemes

• An argument that has certain implicit premises is called an enthymeme. Almost all arguments we actually come across fall into this category.
• Consider:
  • Jane must be sick, since she is not at school and it is not like her to miss school for no good reason.
  • The conclusion “Jane is sick” does follow from the premises. It is implicitly assumed that other good reasons for Jane to be absent (such as a death in the family, etc.) do not obtain.

3.7 The Naturalistic Fallacy

• David Hume famously said that you cannot get an ought from an is.
• That is to say, you cannot derive a normative claim from purely descriptive premises.
• An argument of the form:
  • That is how things are, so this is how things should be.
  • Is said to commit the naturalistic fallacy.
• For example: 
  • The cheetah, the fastest land animal, can only attain speeds of 120 km/h, so humans should not drive more than 120 km/h.
  • As it stands, this argument clearly commits the naturalistic fallacy.

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4. Fallacies

4.0 Glossary Terms

• Ad hominem
• Affirming the consequent
• Defeasibility
• Denying the antecedent
• Equivocation
• Evidential fallacies
• Fallacies
• False dichotomy
• Genetic fallacy
• Implicit
• Logical fallacy
• Modus Tollens
• Post hoc ergo propter hoc
• Quantifier scope fallacy
• Straw man fallacy

4.1 Self-test

1. Denying the antecedent is another name for modus tollens.
   • False
2. "Since I have no evidence that the prime minister died in his sleep two days ago, I'll conclude that it is not true that he died in his sleep two nights ago." This passage involves the fallacy of appeal to ignorance. True or false or can't say?
   • False: This is not a fallacy because it is reasonable to believe that if the prime minister died two days ago, we would know about it.
3. "There should be no publication bans in the case of sensational violent crimes. There is a lot of public interest in these cases, and the media should report on what is in the public interest." This is an example of:
   • Equivocation
4. Arguments involving evidential fallacies are fallacious because they are deductively invalid.
   • False
5. "Researchers working on testing the new drug Teamosil claim that it is completely safe. So we need not worry." This is a fallacious appeal to authority. True or false or can't say?
   • Can't say: Presumably the researchers would have the relevant experience. So the question is whether the result flows from their findings. If they are employed by the company that produces the drug, then we have reason to doubt this. Even if the researchers are not dishonest, getting paid by a company that has a vested interest in the result of a study can influence the result.
6. "Santa Clause is not a symbol of generosity, but a symbol of greed. After all, everyone knows that the modern image of Santa Claus was invented by the Coca-Cola Company." This is an example of:
   • Appeal to popular opinion
7. "The government is pouring heaps of money into safe-injection sites for heroin addicts. These sites do nothing other than contribute to the safety and comfort of criminals. This is clearly misuse of tax dollars." This is an example of:
   • Begging the question/slanting language: This clearly involves many slanted terms such as “pouring”, “heaps” and “criminals”. The first two make the spending seem obviously wasteful. The last, although perhaps technically correct, at least strongly suggests that the way to deal with such people is punishment and not treatment (which is, in part, what the argument means to show). Once the presuppositions involved in these slanted terms are eliminated, there is next to nothing left of the argument.
8. "You say you should be mayor, but you are a drunk whose personal and financial life is in chaos." This is an example of:
   • These are actually some pretty good reasons why this person should not be mayor. It may be insulting, but that does not make it an ad hominem (because what is being attacked is relevant to the claim).
9. "The Liberals, the NDP and the Bloc Québécois all oppose the Conservatives’ plan to purchase new fighter jets. They want us to leave our skies completely defenseless." This is an example of:

* The straw man fallacy: Here an uncharitable position is being ascribed to the opposing parties.

4.2 Unreliable Reasoning

• Logical fallacies
• Evidential fallacies
• Procedural or pragmatic fallacies: A matter of how

4.3 Logical Fallacies

Invalid Conditional Forms

• Affirming the consequence
  • If $P$ then $Q\Rightarrow Q$, then $P$
• Denying the antecedent
  • If $P$ then $Q \Rightarrow$ Not $P$, then not $Q$.

Scope Fallacy (typically includes syntatic ambiguity)

• Everybody likes somebody. $\Rightarrow$ There is somebody whom everybody likes.
• A woman gives birth in Canada every three minutes. $\Rightarrow$ There exists some particular woman in Canada who gives birth every three minutes.

Equivocation

• Take a war on drugs as an actual war.

4.4 Evidential Fallacies

Argument from Ignorance (Argument from Lack of Evidence)

• Description
  • There is a lack of evidence that P, so not P.
  • There is a lot of evidence that P, so P. (invalid, but evidentially reasonable)
• The quality of an argument from lack of evidence depends on how informed we are – how hard we have looked for evidence.
• An argument from lack of evidence is reasonable when it can correctly be framed in the form of a Modus Tollens argument:
  1. If P were true, then we should expect to find evidence that P by investigative means M.
  2. Using investigative means M, we have been unable to find evidence that P. Therefore,
  3. There are good grounds to regard P as untrue.

Fallacy of appeal to vicarious authority

• Professor X said that P. Therefore, P.
• Standards for evaluating expert opinion:
  1. Relevant expertise
  2. Recent expertise
  3. Reason to believe that the opinion flows from the expert knowledge rather than from other commitments or motives
  4. Degree of consistency with broader expert opinion

Fallacy of Appeal to Popular Opinion

• Everybody believes that P. Therefore, P.

Post hoc ergo propter hoc

• After; therefore because of.
• e.g.
  • I walked under the ladder and then my nose bled. Therefore, walking under the ladder caused my nose to bleed.

4.5 Procedural or Dialectical Fallacies

Question-begging

• Any form of argument where the conclusion is assumed in one of the premises.
• e.g.
  • The reason everyone wants the new "Slap Me Silly Elmo" doll is because this is the hottest toy of the season!
  • Explanation: Everyone wanting the toy is the same thing as it being "hot," so the reason given is no reason at all.

Straw man fallacy

• Description: Attacking an argument or view that one’s opponent does not actually advocate. Substituting a person’s actual position or argument with a distorted, exaggerated, or misrepresented version of the position of the argument.
• Form:
  1. Person 1 makes claim Y.
  2. Person 2 restates person 1’s claim (in a distorted way).
  3. Person 2 attacks the distorted version of the claim.
  4. Therefore, claim Y is false.

Ad hominem fallacy

• Description: Attacking the person making the argument, rather than the argument itself, when the attack on the person is completely irrelevant to the argument the person is making.
• Form:
  1. Person 1 is claiming Y.
  2. Person 1 is a moron.
  3. Therefore, Y is not true.
• Example:

  My opponent suggests that lowering taxes will be a good idea -- this is coming from a woman who eats a pint of Ben and Jerry’s each night!

• Explanation: The fact that the woman loves her ice cream, has nothing to do with the lowering of taxes, and therefore, is irrelevant to the argument.

Genetic Fallacy

• Description: Basing the truth claim of an argument on the origin of its claims or premises.
• Logical Form:
  1. The origin of the claim is presented.
  2. Therefore, the claim is true/false.
• Example #1:

  Lisa was brainwashed as a child into thinking that people are generally good. Therefore, people are not generally good.

• Explanation: That fact that Lisa may have been brainwashed as a child, is irrelevant to the claim that people are generally good.

Complex Question Fallacy

• Description: A question that has a presupposition built in, which implies something but protects the one asking the question from accusations of false claims. It is a form of misleading discourse, and it is a fallacy when the audience does not detect the assumed information implicit in the question and accepts it as a fact.
• Example #1:

  How many times per day do you beat your wife?

• Explanation: Even if the response is an emphatic, “none!” the damage has been done. If you are hearing this question, you are more likely to accept the possibility that the person who was asked this question is a wife-beater, which is fallacious reasoning on your part.

False dichotomy

• Description: When only two choices are presented yet more exist.

• Logical Forms:

  • Either X or Y is true.
  • Either X, Y, or Z is true.

• Example (two choices):

  You are either with God or against him.

• There are also those who simply don’t believe there is a God to be either with or against.

Fallacy of Composition

• Description: Inferring that something is true of the whole from the fact that it is true of some part of the whole. This is the opposite of the fallacy of division.
• Logical Form:
  1. A is part of B.
  2. A has property X.
  3. Therefore, B has property X.
• Example #1:

  Each brick in that building weighs less than a pound. Therefore, the building weighs less than a pound.

Fallacy of Division

• Description: Inferring that something is true of one or more of the parts from the fact that it is true of the whole. This is the opposite of the fallacy of composition.
• Logical Form:
  1. A is part of B.
  2. B has property X.
  3. Therefore, A has property X.
• Example #1:

  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.

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5. Critical Thinking about Numbers

5.0 Glossary Terms

• Mean
• Median
• Ordinal numbers
• Percentage
• percentile

5.1 Self-test

3. The term "average" is ambiguous.
   • True: It can mean either mean, median or mode.
4. Jane goes to the casino on Monday and wins a thousand dollars. She goes back Tuesday and Wednesday and wins a thousand dollars each day as well. She reasons that by continuing this practice, in one year she will have made over $350,000. Here she has:
   • Committed the fallacy of linear projection
5. "The ENIAC was the first general purpose digital computer. It was enormous. It took up 680 square feet. Now for less than $680 you can buy a computer that is far more powerful than this." This passage has:

* Made a meaningless numerical comparison: Comparing size in square feet to price in dollars is a meaningless comparison.

5.2 Percentages

• Not (normally) an absolute number.
• Meaningfulness depends in part on the size of the absolute values involved.
• Cannot be straightforwardly combined with other percentages, without knowing and controlling for differences in absolute values.
• Percentage vs. Percentile
  • Percentage 80%: 80% of all
  • Percentile 80th: Better (or worst) than 80% of all
• Ordinal Rankings
  • An ordinal number is a number that tells the position of something in a list, such as 1st, 2nd, 3rd and so on.

5.3 Numerical Issues

Meaningless quantitative comparison

• Which is greater: the mass of the sun or the distance between the Earth and Neptune?

Pseudo-precision

• We have overseen the creation of 87,422 jobs this month. (87,422 cannot be true)

Graphical fallacies

• Spurious correlation
• Unclarity
• Poor or incoherent choices of units/metric

5.4 Linear Projections

• Mean: average
• Median: middle position
• Mode: The most frequently occurring value, could be more than 1 value.

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6. Probability and Statistics

6.1 Glossary Terms

• Confidence interval
• Conditional probability
• Intuitionistic logic
• Standard deviation

6.2 Representative Sampling

• Two broad ways of getting an unrepresentative sample:
  1. Biased sampling does not entail deliberate bias.
  2. Unluck, any means of gathering data that tends toward an unrepresentative sample (relative to the property being measured).
• e.g.:
  1. Baised sampling:
     1. Using a university’s alumni donations address list for a survey on past student satisfaction.
     2. An e-mail survey measuring people’s level of comfort with technology.
     3. A Sunday morning phone survey about church-going.
     4. Solicitations for voluntary responses in general.
  2. Got unluck
     1. Surveying height, we might happen to pick a set of people who are all taller than average or shorter than average.
• How do we rule out being unlucky in this way?
  1. By taking the largest sample we can afford to take.
  2. By qualifying our confidence in our conclusions according to the likelihood of getting unlucky with a sample of the size we chose.

6.3 Confidence and Margins of Error

• When we draw (non-deductive) inferences from some set of data, we can only ever be confident in the conclusion to a degree.
• Significance is a measure of the confidence we are entitled to have in our probabilistic conclusion. It is, however, also a function of how precise a conclusion we are trying to draw.
• Confidence is cheap. We can always be 100% confident that the probability of some outcome is somewhere between 0 and 1 inclusive - at the price of imprecision.
• The more precise we want our conclusion to be, the more data we need in order to have high confidence in it.
• So when we are told the result of some sample, we need to know both the margin of error – that is, how precise the conclusion is – and the degree of significance.
• “a 3% margin of error 19 times out of 20” means have .95 (19/20) probability of getting a result within 3% (on either side) of the reported value.
• Convert our .95 confidence into .99 confidence
  1. increase the margin of error
  2. or get much more data in order to do so.
• if a poll reports a 3% difference in the popularity of two political candidates when it has a +/-3% margin of error at 95% confidence:
  1. The difference is at the boundary of the margin of error.
  2. This does not mean that the difference is nothing.
  3. It does mean that we cannot be 95% confident in the difference.

6.4 Monty Hall Problem

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7. Biases Within Reason

7.0 Glossary Terms

• Cognitive biases
• Confirmation bias
• Self-fulfilling prophecies
• Spin

7.1 Self-test

1. In order for a confirmation bias to occur with respect to some proposition P, one must believe P.
   • False: It need only be salient (present in your mind). If someone suggests something to you, even if you do not believe it right away, confirmation bias is a danger.
2. In cases of confirmation bias for the claim that Scots are frugal, what cases get overemphasized?
   • Scots behaving frugally
3. In order to correct for confirmation bias for the claim that Scots are frugal, what cases should we try to pay more attention to?
   • Non-Scots behaving frugally
   • Scots behaving non-frugally
4. The framing effect is:
   • The effect of how a situation is described on what we believe about it.
5. The existence (and persistence) of many stereotypes can be explained by
   • The repetition effect
   • Confirmation biases
   • The disregarding of sources of information likely to undermine the view
6. Evidential neglect is when you dismiss evidence against a view without properly considering its merit.
   • True
7. Often, when we do not just dismiss evidence that challenges our beliefs, we subject the opposing view to a disproportionate amount of criticism. This is an example of:
   • Moving goal post fallacy
   • Confirmation bias
8. A top-down perceptual bias is:
   • When expectations influence what is perceived

7.2 Perceptual Biases

• Top-down expectation bias: What we expect has an impact on what we believe we are experiencing.
• e.g.:
  1. McGurk effect
  2. Hollow face illusion

7.3 Self-Fulfilling Prophecy

• Description: A self-fulfilling prophecy is a prediction that directly or indirectly causes itself to become true, by the very terms of the prophecy itself, due to positive feedback between belief and behavior.
• e.g.:
  • A palm reader tells Ted that his team will win against a much better team. This gives Ted confidence that he would not otherwise have had, leading him to play a great game. His team wins as a result.

7.4 Representativeness

• One of the reasons we are intuitively poor probabilistic reasoners appears to be that we sometimes lapse into reasoning from representative cases.

7.5 Framing Effects

• Explanation:
  • the way a situation is described can have a powerful influence on judgments about it.
• e.g.:
  • 600 people are sick, 3/2 are going to die.
  • If described as "200 are going to live", acceptable.
  • If described as "400 are going to die", unacceptable.

7.6 Repetition

• Explanation:
  • The repeated claim can come to just “seem true” or strike us as reasonable if we have heard it again and again.

7.7 Biased in favour of confirmation

• Explanation:
  • If you believe something, then you are likely to treat neutral evidence as confirmation of your belief. Confirmation biases are extremely common.
  • When you expec1t (consciously or not) some outcome, this can create a confirmation bias.
  • Any tendency of thought or action that contributes to a salient proposition’s seeming more warranted than it is.
• e.g:
  • A palm reader tells Ted he will play better than normal in the game. Ted plays normally, but each of his good plays strikes him as particularly significant in light of the prediction. He believes he has played better than normal.
  • Even if you are entirely convinced that walking under a ladder cannot bring about (non-ladder-related) misfortune, just being aware of the superstition’s existence can make a misfortune seem more noteworthy if it happens after you walk under a ladder (or break a mirror, etc.).
  • Seeing resemblances between a newborn boy and his parents.
  • Suppose you believe that Scots are very frugal. Then the cases in which you see a Scot doing something to save money will strike you as particularly significant.

7.8 Biases toward evidence supporting the belief in question

• Top-down effects on perception
• Biases in evidential search methods.
• Structural biases.

7.9 Biases toward evidence undermining a belief

• Evidential neglect: when you dismiss evidence against a view without properly considering its merit.
• Disproportionate criticism.
  • Moving goal post fallacy: apply different standards to views you agree with and views you disagree with.

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8. The More We Get Together

8.0 Glossary terms

• Bandwagon effect
• False consensus effect
• False polarization effect
• Fundamental attribution error
• Leveling
• Sharpening

8.1 Self-test

1. Optimistic self-assessment is what we call applying different standards when examining your own behaviour than you do when examining the behaviour of others.
   • True
2. Fundamental attribution error is when you mistakenly view all people as either fundamentally good or fundamentally bad.
   • False: The fundamental attribution error is when you explain an instance of someone's behaviour in terms of a character trait while ignoring any contextual explanations.
3. Liberals who believe that conservatives want to institute a pseudo-fascist state or conservatives who think that liberals are mostly Marxist-Leninists are examples of (choose the best description):
   • False polarization
4. False polarization involves making an accurate representation of your own view while making a false representation of your opponent’s view.
   • False: In a false polarization your own view is also represented as closer to the stereotyped position than it actually is.
5. The bandwagon effect affects only what people say they believe; it does not actually affect what people believe.
   • False: It actually affects not just the views that are expressed, but also what people actually believe.
6. The error of assuming that people are in general agreement with you on an issue (when you have no evidence for this) is called:
   • The false consensus effect
7. The false consensus effect:
   • Is explained by optimistic self-assessment
   • Involves taking other people's silence as an expression of agreement
   • Explains, for instance, why someone might be shocked when his/her superiors (with whom he/she has a fairly friendly relationship) vote to replace him/her
8. Your chances of engaging in the biased reasoning discussed in this chapter can be reduced by:
   • Considering why someone might reasonably disagree with your position
   • Encouraging others to express contrary positions
9. Sharpening is when someone adds to a story in order to make it sound more sensational
   • Sharpening is often unconscious and is often a result of someone honestly trying to retell the story with the same point as he/she interpreted the original teller of the story to have.
10. If someone says something that can be checked fairly easily, it is reasonable to conclude that it is true since if it were a lie, it would be exposed.
    • False

8.1 Social Cognition

• Explanation:
  • The existence of other people in a reasoning context and the nature of our relations with them apply to our judgments and inferences in two broad ways:
    1. Reasoning about other people.
    2. Reasoning influenced by them.

8.2 Reasoning About Other People

• Common forms of poor reasoning about others have a few shared characteristics:
  • Optimistic assessment of ourselves.
  • Idealized/oversimplified theorizing.
  • Overemphasis on character rather than context.

8.3 Fundamental Attribution Error

• Explaining “local” behaviour in terms of broad character traits while overlooking local situational explanations.
• When we reason about others, we often make the FAE. When we reason about ourselves, we tend to make the error of optimistic self-assessment.

8.4 False Polarizatio Effect

• Overestimating the differences between one’s own view and the view of someone who disagrees by interpreting the other person’s view as closer to the “polar opposite” than it actually is.

7. "Optimistic Self-Assessment" Plus Oversimplification

8. How Reasoning About Others Entrenches False Polarization

9. A Fallacy Related to False Polarization

10. Bandwagon effect

• When all or most people in a group are in agreement, it is much more difficult to hold a dissenting view.
  • Pressure against expressing dissent creates pressure against dissenting belief

11. False consensus effect

• Overestimating the extent to which others share one's perception of a situation.
• Interpreting other people’s silence as indicating their agreement.
• Optimistic self-assessment again
  • Take our perspective to be accurate.
  • Interpret silence as agreement.
  • Take the imagined agreement as confirmation.
  • Regard our view as strengthened by numbers.

13. Mechanisms of False consensus

14. The Flow of Information Through Groups

15. Experimental Evidence for Leveling and Sharpening

16. Key Points About Leveling and Sharpening

17. The Interpretation of Socially-Transmitted Information

18. Commonly Overestimated Social Effects on the Flow of Information

19. A Related Concept

20. Few Contexts of Communication are Widely Policed

21. Why do False Stories Spread

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9. Critical Reasoning about Science

9.0 Glossary terms

• Falsifiability
• Verifiability
• Pseudo-science
• Scientific method

9.1 Self-test

1. Scientists have special training which allows them to easily avoid the various biases and other reasoning errors we saw in the previous lessons.
   • False: Scientists are guilty of all of the same errors as the rest of us, but science is a context where individual error can be corrected.
2. Science must be
   • There is no single unifying feature that all science has.
3. Even if not all science needs to be falsifiable, unfalsifiability is a hallmark of pseudo-science.
   • True
4. The view that scientists are a unified group of dogmatic and like-minded people is often how proponents of pseudo-scientific theories explain their theory's lack of general acceptance
   • False: Science is a large and diverse enterprise. Certainly, not every bias is factored out, but there is usually room for serious disagreement.
5. Scientists may be tolerant of opposing views, but they would never take any claim about, for example, the existence of ESP, very seriously.
   • False
6. You design a study to look for the influence of A on B and find no conclusive results. You notice that there is a relation between A and C in the data. If you conclude that A is related to C, you then:
   • Are guilty of the multiple endpoints fallacy
7. A confound is
   • An alternative explanation
8. The influence of pharmaceutical companies on science is:
   • A clear source of bias that needs careful attention in order to examine its influence

9.2 The Function of Science

• We have seen reasons to expect problem with: deductive reasoning, inductive reasoning, data selection, testimony, media, our own perceptions, our own memories, our own interpretations of data.
• How can we get around this?
• What is needed is a context of inquiry in which the prospect for momentary individual error is factored out by a requirement of repeatability.
• The prospect of individual systematic bias is constrained by a requirement of replicability by any competent practitioner.
• The silencing result of false consensus effects and social pressures against assertions are explicitly set aside:
• There are explicit conventions that favour nothing confounds and questioning outcomes.
• The prospect of systematic group biases is constrained by the openness of the practice to anyone who can attain competence in it. (NB: this supports at least one feminist critique of science as traditionally constituted.)
• In short, this is what science is all about: it is a set of practices valuable for their effectiveness in minimizing the effects of any one specific error or bias.
• There is no tidy description or recipe that explains all of these practices. Many are domain-specific or vary in importance from discipline to discipline.

9.3 Characteristics of Science

• Verifiability: Verifiability is a hallmark of science. In the simplest terms, science differs from non-scientific areas of human activity because in science we actually check to see if our claims are true.
• Falsifiability: Science differs from pseudo-science in making clear predictions. If the prediction does not come out true, we reject the theory. Unfortunately, even good science does not conform to Popper's strict views on falsifiability.

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10. The Mainstream Media

10.0 Glossary terms

• Bias
• Infotainment
• Mainstream media

10.1 Self-test

1. If someone owns a newspaper (and plays an active role in running it) and supports political party A, then it would be surprising if he or she:
   • Does not skew the content in favour of portraying Party A in a positive light
2. The difference between the headlines "Rock faces new conflict of interest charges" and "Rock defends Irving trip" are important because of what concept from a previous chapter?
   • Framing effects
3. Almost all news programs have only a handful of investigative journalists.
   • False: Many news programs do not have any investigative journalists. They get their news from the news wire (press releases) and from other news sources.
4. An editor plays a role in biasing journalism only if he or she rejects stories because of their content or demands that stories be significantly altered because he or she is displeased with the content.
   • The biasing factor may be more subtle. A reporter will, consciously or not, often know of the editor’s views and seek to please him or her.
5. Embedded reporters have much greater access to the events they seek to cover at little to no journalistic cost.
   • Embedded reporters depend for their information on a secretive and (often for good reason) deceptive group. What they may gain in terms of fairly secure access to a war zone comes at a significant journalistic cost.
6. Advertisers for major news programs play an active role in deciding the content of the news stories for that show.
   • The influence is not that direct. They do not get to say that this gets reported and that does not, but they can pull their advertisements if they are unhappy with certain aspects of the program.
7. Military analysts are former military personnel who often have an undeclared vested interest in the case they are hired to discuss.
   • They often work for companies with large military contracts.
8. The rise of celebrity and other sensational news is the fault of both the news corporations and of the general public.
   • True
9. Celebrity and other sensational news complement regular news stories, adding some diversity to news programs.
   • False: While this may have at one time been true, this now poses a serious threat to an informed public.
10. The decline of serious investigative journalism leads to:
    • Greater dependence on press releases
    • More homogeneity in the news
    • Pseudo-independent confirmation

10.2 Mainstream Media

• Mainstream media: In aggregate, another channel for information that is far less governed by truth-preserving and truth-favouring norms than one might uncritically assume.
• Even media that purport to be deliverers of news, science, history - in short, actual events - are subject to many powerful norms distinct from, and often inimical to, those of accuracy and relevance.
• Interaction of public biases with commercial motivations of (broadly construed) news media:
  • Emphasizing celebrity news
  • Appealing to preconceptions of many sorts
  • Minimizing events in areas of which the audience is ignorant
  • Indulging the desire to be thrilled by sex, violence, outrage, fear, mystery, irony, a sense of the miraculous
  • ...at the expense of accuracy and significance in many cases.

10.3 Personal Biases in the Media

• Present at all levels of media workers.
• Most significant at the editorial and ownership levels.
• These people choose the content and have the power to hire, fire, promote and raise the pay of reporters.

10.4 Commercial Biases in the Media

• Advertisers' aims and fears play a powerful role in the thinking of owners and editors.
• Profit motive selects for homogeneous fact-gathering: the use of wire services and press releases.
• Different media outlets may then differentiate their coverage through spin, punditry and peripheral features (e.g., the look of the "ticker" on CNN, CBC, FOX, etc.).

10.5 Infotainment

• Frivolous reporting masquerading as, or at least substituting for, real journalism.

10.6 Competence Issues

• Science, politics, history, law...often these are complex matters that journalists are ill-prepared to summarize accurately.

10.7 Bias Issues

• Typically apply most strongly at the level of ownership and editorship; reporters are mostly just trying to remain employed.
• Can be overt (direct orders on how to slant reportage) or subtle (the various cognitive and social biases that influence reporters and editors to please those above them).
• Vested interests in reporting:
• Business reporters/pundits
• "Based on"
• A meaningless qualifier; implies nothing as far as accurate representation of any true events.
• Feedback loop between information consumers and information providers? Perhaps the more infotainment we get, the more we want - or, at least, the more it is true that infotainment is all we can handle.

10.8 Media diversity: Broadening or Narrowing Perspective?

• A plurality of media sources/viewpoints seems as likely to enable the selection of homogeneous sources as to encourage broad opinions.
• Contributing to informationally divided sub-populations.