Inference #3 – Sign

We’ve covered a lot of ground since the Critical Discussions topic started on 9/26. You can go through the contents of this blog since then to refresh yourself. We have talked about:

- Developing a concise understanding of the controversy (resolution)
- Ways to formulate questions about the controversy (issues)
- The four kinds of Claims (Fact, Definition, Quality, Policy)
- The three kinds of Evidence used to support claims (Credibility, Social Consensus, and Objective)
- The six kinds of Inference to connect Evidence to Claim (Example, Cause, Sign, Analogy, Narrative, Form)

Please review the info posted since 9/26/2008. Also, I posted a pictorial of this model here for you to view. It may help explain the relationships

After we get through the next three inferences, we will be moving into some “How To” in more advanced territory. Namely, HOW to raise issues so that the discussions progress smoothly, even in tricky situations or with touchy topics; HOW to keep a discussion tracking, even when it is emotional; and HOW to remain collaborative, even when the other parties want to compete.

This week, we will talk in detail about the third strongest type of inference – Sign.

Recall that last week I wrote about Inference from Cause, in which a predictable relationship between two variables is asserted AND the relationship is described as one variable CAUSING a change in the other.

Inference from Sign is not as strong in that there is no intention to EXPLAIN the relationships - just to declare that the relationship exists. In other words, Inference from Sign occurs when the link between evidence and claim asserts a predictable relationship between variables WITHOUT accounting for it. This is also called a correlation; an observation is made that when one thing changes (students studying, for instance) and some other thing happens (getting good grades). Do we KNOW that studying causes good grades? If a student didn’t study would they still get good grades? A percentage of them would, and the strength of the correlation would be affected by other mitigating variables (what subject, the student’s familiarity with the subject, the success of the teacher in delivering the information WITHOUT study, etc.). We may not be able to show that students that study will necessarily get good grades because studying by itself is a CAUSE of good grades, but we CAN show that students that study get good grades. So an inference from sign says that “I can show that when one thing occurs, then another thing predictably happens, and that is enough to substantiate my claim”. Here is an example:

Tom – “I think I can prove to you that my marketing idea will work.”
Bob – “How are you going to prove it?”
Tom – “I hired an expert to look it over and she says it's great.”
Bob – “What makes her an expert?”
Tom – “She has a college degree.”

Tom’s claim – This marketing idea will work
Tom’s evidence – Expert opinion
Tom’s inference – A college degree is a sign of expertise

Let’s say that we agree that a college degree is a sign of expertise. Is that enough to uphold the claim? Not for me. Can you think of a few questions that Bob might add?

By this time, you should be thinking of the right questions to ask. When you use these methods, you should be anticipating the questions you may ask others and the questions you might be asked.

How about these questions:
- Has she rendered expert opinions before and been right?
- Has she rendered expert opinions before and been wrong?
- Are there other experts that agree with her?
- Are there other experts that disagree with her?
- Does she stand to gain from rendering a positive opinion?
- Does she stand to lose from rendering a negative opinion?
- Does she stand to gain from rendering a negative opinion?

These are all good questions. They ask about the credibility of the source and her bias (does she have a long history of being right?; are there other equivalent experts and will they back up her opinion or shoot it down; is she biased- saying what you want to hear to get paid? or is she doing the opposite and risking telling you what you don’t want to hear (thereby increasing her credibility)?

The questions are NOT aimed at the validity of the inference itself, though. To question an inference, you must question the INFERENCE. Questions about the inference ONLY ask "Has the evidence been properly linked to the claim?"

Questions aimed at the INFERENCE (a college degree is a sign of expertise) would be these:
- Do people without college degrees have sufficient expertise to render expert opinions? (If people without college degrees can render this kind of opinion, then her degree is not significant in this instance)
- Do people with college degrees generally have sufficient expertise to be able to render meaningful opinions about this kind of marketing question? (If people with college degrees usually do not have sufficient expertise to render a meaningful opinion, then her degree is not significant in this instance)

The first set of questions is about the source's CREDIBILITY and BIAS. You could ask all of them whether or not she has a degree.

If we question the inference and the result is that “Usually, a college degree is sufficient indication of expertise to render opinions in a matter like this”, THEN you can ask about credibility and bias. If not, why bother? That would be the time to find out if there is any other inference that she could provide - like maybe some Letters of Reference (another Inference from Sign) or maybe some samples of other marketing opinions she has rendered (inference of example - much stronger)?

If you accepted the college degree as a sign of expertise, there are two more questions that you would ask in this case (and in any case when the inference from sign is describing a sign of expertise):

- Is the degree of a sufficient level and in a relevant subject to render the opinion? (An associate’s degree in zoology is probably not sufficient for marketing opinions)

and

- Is the degree from a reputable college?

Also remember that this is not an Inference from Cause. No one is claiming that a college degree CAUSES you to be capable – it is just describing a correlation between college degrees and capability.

As with Cause, there are numerous mathematical methods used to show statistical correlation. Please search the internet for “statistical correlation” to see if those are what you need.

The classic tests for Inference from Sign are:
- Does the sign usually appear with the thing signified (ex: college degree and expertise)?
- Does the sign frequently appear without the thing signified (ex: college degree and incompetence)?
- Are there countersigns (absence of college degree and expertise)?
- Could the correlation be a coincidence?
- Is it really a causal relationship?

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