What is a Good Enough Scientific Proof: A Brief Discussion of Four Examples?
This paper deals with statements about scientific proof. I assert that the type of scientific proof needed to prove a statement depends upon that statement. I also assert that good enough scientific proof is likely to vary based on the problem. I wish to note again that the following post deals only with statements, not with designing actual research questions/hypotheses/surveys. I will discuss one issue that I consider to be more of a hindrance that a help and will advocate the importance of specificity. I will use four examples to help demonstrate these issues.
Good enough scientific proof will likely have these elements in common: An empirical approach to the question, along with the objective measurement and manipulation of variables. To a lesser extent this is also true for control of extraneous variables, social importance, and method of analyzing data.
The Four Examples
Statement 1. God exists.
There are variables here that can not be objectively measured/assessed (with apologies to Thomas Aquinas). Whether or not this is true, this is not a matter science can deal with in the first place. I give this as an example of a question outside the range of the current topic.
Statement 2. When I throw a ball at the window, the window breaks.
This is not an issue that I would expect most persons to demand a scientific proof for at all. I think that most of us have either done this ourselves, read about it, or have seen it. However, I wish to use this example draw in the problem of argument by common sense in the establishment of a scientific proof. I expect that some of us would pass this problem off as a common sense “no kidding” sort of answer. However I want to show the limit of that approach. I won’t make this banal by demanding that we specify the exact speed of the ball and whether it was pitched under or over hand and at what distance from the window plus elevation.
I will however, ask that the reader entertain the problem of another sort of window. This window is in a school building and is wire mesh reinforced. Will this break too? Quite likely the answer is “yes”. However, now there is a greater deal of uncertainty than in the former problem. The common sense equation that “Chuckin’ a ball at a window results in a broken window” now seems to be fallacious and it is certainly not scientific. This, issue could well be a concern for those who manufacture such windows and the schools who buy them. This could provide a statement that science could assess. It also shows the importance of specificity.
Statement 3. On a plane trip to Europe, many passengers become violently ill. Lab analysis results indicate that staphylococcus bacterial toxin was involved. Only those passengers who ate breakfast on the plane became ill. A cook for flight had a cut on his hands and handled the food without the benefit of gloves. The cut possibly harbored the bacteria which promulgated in the food leaving behind their toxins, thus causing this point epidemic.
This situation provides likelihood, but not certainty. The investigation that led up to it, was probably thorough and likely even scientific, but it does not provide such specificity in the statement given. In this case I would ask for a more thorough assessment that the bacteria did in fact come from the cut on the cook. I would ask this because, it is highly important to know with great certainty where the bacteria came from, so as to prevent illness/harm to future passengers. The details are socially important here and to add that needed proof we should attempt to rule out other sources of bacterial movement into the food as well as doing a swab and culture on the cut of the cook’s hand.
Statement 4. The use of this diet is correlated to the downward trend of hyperactive behavior in children who are on it.
This is probably fine; the authors of the statement have noted that the two variables are correlated as opposed to saying that one caused the other. The authors of a statement would have to be on guard to make sure that others who may not have a research background understand that correlation is not causation. It is also important in this case that the correlative design be well designed and appropriate to the issue. Such specific details matter here too.
Specificity allows us to decide if the statement is appropriate based on the proofs given. Good specificity answers who, what, when, where and why and under what conditions for each.