FROM FACTS TO POLICIES

How to Sift through any Issue

 

KINDS OF

KNOWLEDGE

KINDS OF QUESTIONS

 

 

FACTS

What is it? What exists or is real out there?

 

What is verifiable?

 

 

DEFINITIONS

What kind(s) or units are there of those facts?

 

What do you mean by x?

 

 

INFERENCES

What can we conclude about these facts?

 

How can our data be presented (transformed) to reveal conclusions?

 

What will be? What can be predicted from this data?

 

 

 

THE SCIENTIFIC METHOD STOPS HERE

 

 

VALUES

What is good or bad, right or wrong?

 

Which has top priority?

 

What are our criteria for good, better, best?

 

 

POLICIES

What should we do?

 

What are all our alternatives?

 

 

 

 

A: Questions of fact and definition work together. We don't have a fact until we define our terms. The number of students in the class changes with our definition of "in the class"--present today, enrolled, etc. In principle, if all features of the data gathering remain the same, any other researcher will get the same raw data.

 

 

B: The manner in which those facts are handled is crucial to the kinds of inferences one might draw from them. Put into a database, therefore, different transformations/selections of the same data are possible, using standard or acceptable definitions.

 

 

C: At some point inferences can step into the future (we call them extrapolations). At that point, assuming changes, we can begin to form a new hypothesis that is testable and begin the process over OR we simply enter the realm of speculation which is beyond the scientific method.

 

 

D: Questions of Value are prominent in a life where we make choices, show preferences, or have tastes of our own or our culture's. Establishing CRITERIA helps clarify values the way good definitions substantiate the facts. If we agree that the most valuable baseball player is the one with the most RBI's, we can settle the issue with facts; if leadership is the major criterion, then we have another value to weigh.

 

 

E: The most complicated kind of question is what to do. Each alternative has to be evaluated: what inferences can we expect (how will the data change if we do this?) and which values are most likely to accrue. Making a priority list of values and trying carefully to define exactly what the problem will help us focus the search for alternatives.