Paradigms

Last Saturday and Sunday I attended my 3rd weekend long seminar for my Autism course. We discussed program models in great detail, and there was much debate about the effectiveness of each model. The two models that caused the most debate were the UCLA model (Lovaas) and the Verbal Behavior (VB) Model (Sundberg et al).

The UCLA model has been replicated a number of times, and has multiple research articles that provide consumers with the effectiveness of the model. The VB model does not have the luxury of the replication data possessed by the UCLA model, which caused a few students to be concerned.

Question 1: Should we adopt a model that does not have the scientific background that it's "opponent" does?

Most people won't have trouble answering this question. A majority of new, up-and-coming scientists see this as an obvious... of course you shouldn't! However, this conclusion isn't as obvious to me.

Let's explore the following questions:

1. Is a science a good science if and only if it has data that supports it? The answer to this question is NO. Here's why: any "science" can call itself "good science" by showing that it has data. Years ago, we had the nice, hard, scientific proof that showed that White Males were far superior to African American males. Why? Because the White males had a brain size significantly larger than African American males. At the present time, scientists have rejected this statement; good data doesn't mean good science.

2. Is a science a bad science if and only if it does not have data that supports it? Again, the answer to this question is NO. Why? Because every science has emerged from nothing, and as it emerges, it has no data. After a while, data is collected and analyzed accordingly. Never, when a new science emerges, do we say "It's a bad science because it does not have data." That's a self-destructive statement, and because of that, you cannot call a science a bad science on the above premise alone.

What separates good science from bad science is a wonderful philosophical debate that is much more complicated than what I have discussed here. However, it is in my opinion and within my frame of logic that an individual cannot debunk something that does not have data solely on the fact that it does not have data. Alternatively, just because something has data does not mean that it is a good, pure science (again, whatever a "good, pure science" is, is a major philosophical issue).