RE: Earth Rotation and the Flood

Kevin L. O'Brien (klob@lamar.colostate.edu)
Tue, 13 Oct 1998 11:20:45 -0600

Greetings Art:

I am never offended by someone voicing their personal, as long as that opinion is not personal, so don't worry on that score. Unfortunately the way you seem to being using the word bias in this case does imply something wrong. You rejected an explanation for why your fossils are no serious challenge to current rhythmite deposit theory by invoking bias rather than showing how their explanation is wrong. Your implication certainly seems to be that they are making an unscientific use of bias. I am simply trying to suggest that was not the case, so perhaps it would be better to analyze their argument rather than dismiss it as biased.

As for my colleagues and myself, we use multiple working hypotheses all the time; we have to, because the system we study is too complex to support just one hypothesis. Yet which ever is our individual personal favorite (and you ought to sit in our arguments, er, discussions, sometime), we still tend to put aside our biases and let the data do the talking.

Scientists may in fact entertain multiple working hypotheses more often than might seem obvious to an outsider (even a scientific outsider). One reason for preferring one hypothesis over another is that it cuts down on the money and manpower needed to study a particular phenomenon. That does not mean, however, that alternative hypotheses are not discussed or occasionally test for. Another reason is that if you try to publish a paper listing all the different hypotheses that could explain a phenomenon, most reviewers will send it back saying we should resubmit it when we have a better idea of which is the most likely. So there are many more factors than just bias or the rush to publish that might cause a scientist to prefer one hypothesis over others, but he is a fool if he ignores or discounts them.

By the way, it was never my intention to claim that I or anyone else is bias-free and that you or anyone else is not. All I am saying is that good scientists characteristically ignore bias when interpreting data. Nothing more.

Kevin L. O'Brien