A Workbook For Arguments, Part 3: Analogies, Sources, Causal Claims, and Theoretical Virtues… Oh My!

56.-The-power-of-the-analogy

In this series, I walk through the critical thinking rules that are sections of the book A Workbook for Arguments: A Complete Course in Critical Thinking. The information presented in this series derives largely from the aforementioned source. Nevertheless, paraphrases and original examples are mixed into the posts alongside the content derived from the book.

Arguments by analogy, rather than multiplying examples to support a generalization, argue from one specific example to another, reasoning that because the two examples are alike in many ways (or some particular way(s)), they are also alike in one further specific way.

For example, here is how a doctor might argue that everyone should have a regular physical checkup:

People take in their car for servicing and checkups every few months without complaint. Why shouldn’t they take similar care of their bodies?

This argument suggests that getting a regular physical checkup is like taking your car in for regular servicing. Cars need that kind of attention — otherwise, major problems may develop. Aren’t our bodies like that too? The argument amounts to:

People should take their cars in for regular service and checkups (otherwise major problems may develop). People’s bodies are like cars (because human bodies, too, are complex systems that can develop problems if not regularly checked up). Therefore, people should take themselves in for regular “service” and checkups too.

Notice the italicized word “like” in the second premise. When an argument stresses the likeness between two cases, it is very probably an argument from analogy. Here is another striking example.

An interesting switch was pulled in Rome yesterday by Adam Nordwell, an American Chippewa chief. As he descended from his plane dressed in full tribal regalia, Nordwell announced in the name of the American Indian people that he was taking possession of Italy “by right of discovery” in the same way that Christopher Columbus did in America. “I proclaim this day the day of the discovery of Italy,” said Nordwell. “What right did Columbus have to discover America when it had already been inhabited for thousands of years? The same right I now have to come to Italy and proclaim the discovery of your country.”

Nordwell is suggesting that his “discovery” of Italy is like Columbus’ “discovery” of America in at least one important way: both Nordwell and Columbus claimed a country that already had been inhabited by its own people for centuries. Thus, Nordwell insists that he has as much “right” to claim Italy as Columbus had to claim America. But, of course, Nordwell has no right at all to claim Italy. It follows, then, that Columbus had no right to claim America.

Nordwell has no right to claim Italy for another people, let alone “by right of discovery” (because Italy has been inhabited by its own people for centuries). Columbus’ claim to America “by right of discovery” is like Nordwell’s claim to Italy (America, too, had been inhabited by its own people for centuries). Therefore, Columbus had no right to claim America for another people, let alone “by right of discovery.”

How do we evaluate arguments by analogy? The first premise of an argument by analogy makes a claim about the example used as an analogy. Remember Rule 3: make sure this premise is true. It’s true that cars need regular service and checkups to keep major problems from developing, and it’s also true that Adam Nordwell could not legitimately claim Italy for the Chippewa.

The second premise in arguments by analogy claims that the example in the first premise is like the case about which the argument draws a conclusion. Evaluating this premise is harder, and needs a rule of its own.

Rule 12: Analogies require relevantly similar examples

Arguments by analogy do not require that the example used as an analogy be exactly like the example in the conclusion. Our bodies are not just like cars, after all. We are flesh and bone, not metal; we have neither wheels nor seats nor windshield wipers. We have brains (well, some of us do…). Analogies require relevant similarities. The precise composition of cars is irrelevant to the doctor’s point. The argument is about the upkeep of complex systems.

One relevant difference between our bodies and cars is that our bodies do not need regular “service” in the way our cars do. Cars regularly need oil changes, new pumps or transmissions, and the like. Replacing body parts or fluids is much rarer: think organ transplants or blood transfusions. On the other hand, it’s true that we need regular checkups — otherwise problems can develop undetected — and older and strenuously used bodies, like older and higher mileage cars, likely need checkups more often. So the doctor’s analogy is partly successful. The “service” part is somewhat weak, but the checkup part is persuasive.

Likewise, twentieth-century Italy is not like fifteenth-century America in every respect. Italy is known to every twentieth-century school child, whereas America was unknown to much of the world in the fifteenth century. Nordwell is not an explorer, and a commercial jet is not the Santa Maria.

Importantly, though, these differences are not relevant to Nordwell’s analogy. Nordwell simply means to remind us that it is senseless to claim a country already inhabited by its own people. Whether that land is known to the world’s schoolchildren, or how the “discoverer” arrived there, is irrelevant. The more appropriate reaction might have been to try to establish diplomatic relations, as we would try to do today if somehow the land and people of Italy had just been discovered. That’s Nordwell’s point, and taken in that way his analogy makes a good argument.

In conclusion, when evaluating and analyzing an analogy, ask the following:

In what ways are the two things similar? Are these similarities relevant or irrelevant to the desired conclusion?

In what ways are the two things different? Are these differences relevant or irrelevant to the desired conclusion?

The key is that X and Y must be relevantly alike in order for an argument by analogy using X and Y to succeed.

Sources and Causes

In the final section of this Workbook For Arguments, let’s look at critical thinking in relation to sources and causation.

For sources, be sure that your sources are informed, impartial, independent, and cross-checked.

With respect to causes, it is important to know that nearly all causal claims start with correlations. All of the following may be the case:

E1 may be correlated with E2 because E1 causes E2.

E1 may be correlated with E2 because E2 causes E1.

E1 may be correlated with E2 because E1 and E2 are both caused by or correlated with some third thing, E3.

Finally, the correlation between E1 and E2 might just be a coincidence, with no causal connection between them.

Another crucially important aspect of causal claims is the notion of multiple causation. In many cases, physical, psychological, sociological, cultural, biological, and historical phenomena have many different causes that each contribute to the overall effect. For instance, to say the sole cause of the Civil War was slavery is an oversimplification. While disputes concerning the legality and morality of slavery were the predominant cause of the Civil War, a variety of other causal factors were at play as well. The concept of multiple causation is particularly relevant in this case. Such factors include the election of Abraham Lincoln, Bleeding Kansas, increased sectionalism and regional tension, differences in economy and society, economic considerations involving trade, and much more.

Additionally, causes and effects may interpenetrate. For instance, open-mindedness leads to reading more, and reading more leads to open-mindedness.

Questions to ask when evaluating and analyzing causal claims are as follows:

(1) Is a correlation really present?

(2) What are potential explanations of the correlation?

(3) Which explanation of the correlation is the best?

(4) If an explanation or cause is identified, ask: by what mechanism does this occur? In other words, how does this occur?

Consider the following causal claim:

Eating dinner together with a family leads to greater emotional health in teenagers.

  • It could be that greater emotional health actually increases the likelihood and willingness of teens to eat with their families (or to encourage familial bonding).
  • It could be that greater emotional health actually leads to eating with family more, and then eating with family more, in turn, contributes further to emotional well-being (a loop of cause-effect-cause).
  • It could be that a third causal factor leads to both greater emotional well-being in teens and an increase in family dinners, such as a loving, stable, and supportive family (and familial life).

Evaluating Theories and Hypotheses

To evaluate a theory or hypothesis for its explanatory/theoretical virtues, use the following tools.

Simplicity: How many entities are postulated? How many types of entities are postulated? What is the nature of the entities? Are there arbitrary, unprincipled, or brute propositions or entities to which the theory or hypothesis is committed?

Also look at the amount and complexity of the claims made by the theory.

Simplicity is principally judged by ontological commitment: theories that cover the data with fewer entities postulated are (in general) more likely to be true.

As stated in another post, evaluating theories and hypotheses also requires taking into account: intrinsic probability, coherence, and explanatory scope.

Allow me to unpack these a little bit further. The greatest hypothesis or explanation is the one with the overall greatest balance of intrinsic probability and accuracy.

By “intrinsic probability” of a hypothesis, I mean the probability independent of the evidence we have for or against it. The intrinsic probability of a hypothesis is determined entirely by its modesty and coherence.

By “accuracy” of a hypothesis, I mean the degree to which a hypothesis’ predictions correspond to reality. We measure accuracy by looking at “evidence.”

By “evidence” I mean something which makes a hypothesis more probable than it would have been otherwise. Let me give you an example. Imagine you have two jars of red and blue jelly beans. In the first jar, 90% of the jellybeans are blue and the rest are red. In the second jar, 90% of the jellybeans are red and the rest are blue.

Now imagine you are handed a jelly bean from one of the jars, but you don’t know which jar it came from. If it’s a blue bean, that’s evidence it came from the first jar, not the second. The blue bean doesn’t disprove that it came from the second jar because the second jar also has blue beans. Nevertheless, it’s more likely that it came from the first because there are more blue jelly beans in the first than in the second. Similarly, if it’s a red bean, that’s evidence it came from the second jar.

Mathematicians have a formula called Bayes’ Theorem that can be used to specify the relationship between intrinsic probability, accuracy, and the overall or final probability of a hypothesis. It follows from Bayes’ Theorem that a hypothesis is probably true just in case it has a greater overall balance of intrinsic probability and explanatory power than do its alternatives collectively.

Intrinsic probability is determined by modesty and coherence. By “modesty,” I mean a measure of how much the hypothesis asserts. The more a hypothesis claims, the more ways there are for it to be false and so (before we start looking at evidence) the less likely it is to be true.

By “coherence,” I mean a measure of how well the parts of a hypothesis fit together. If the different parts count against each other, the hypothesis is less coherent and less likely to be true.

Bayesian probability assigning is all about looking at competing hypotheses and asking whether we would expect the data given the hypothesis — in which case the data is evidence for the hypothesis — or whether we would be very surprised by the data given the hypothesis — in which case the data is evidence against the hypothesis.

With all that out of the way, the series is now finished. I really hope you enjoyed it and found it both helpful and enlightening!

Author: Joe

Questions? Ask away at NaturalisticallyInclined@gmail.com

1 thought on “A Workbook For Arguments, Part 3: Analogies, Sources, Causal Claims, and Theoretical Virtues… Oh My!

  1. Pingback: An Index of Blog Series! | Majesty of Reason

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