Animal Rights

Dr. Ray Greek: History and Future

| by Dr Ray Greek

When Dr Shanks and I wrote Animal Models in Light of Evolution our goal was to provide an internalist examination of the issue of using animals as predictive models for human response to drugs and disease. In Animal Models in Light of Evolution we quote Morrell who explains externalism as:

The view that social, political, and economic circumstances affect the pursuit of knowledge of nature... Externalist historians are interested in scientific groups (both institutionalized and informal), the reasons for the development of certain kinds of scientific research, scientific careers and patronage of science. They claim social and economic circumstances have affected the rate and the direction of some scientific work. Committed externalist historians usually assume that the response to such circumstances has on occasion helped constitute scientific knowledge itself. [(Bynum, Browne and Porter 1981) p145]

By contrast, Morrell explains internalism as:

The view that science is primarily an abstract intellectual enterprise insulated from social, political, and economic circumstances. Internalist historians focus on the obviously intellectual aspects of the setting and solving of problems concerned with the understanding and control of the natural world; they highlight conceptual frameworks, methodological procedures, and theoretical formulations. For these historians, often concerned to defend science as the supremely rational form of thought, changes in past science were exclusively or chiefly occasioned by the solving of inherited and abstract problems within a particular field of inquiry. [(Bynum, Browne and Porter 1981) p211]

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Ours was an internalist examination. From Animal Models in Light of Evolution:

While we do not pretend that the distinction between internalist and externalist analyses of the history and practice of science is always straightforward or easy to draw, our approach in this volume is located primarily within the internalist framework. What does this mean? First and foremost we are concerned with conceptual frameworks, methodological procedures and theoretical issues surrounding research practices in the biomedical sciences. Our analysis is self-referential or reflexive in that we intend to examine extant scientific research practices using scientific concepts, methods and theories.


The central concern of this book is with the use of animal subjects as predictive models of human biomedical phenomena.

The above is relevant to the current discussion with LifeScientist and Dr Ringach as our purpose in writing Animal Models in Light of Evolution and in forming Americans For Medical Advancement was to present our position that animals cannot predict human response to drugs and disease. Period. Ours was an internalist examination as was my intent in writing these blogs. Suffice it to say that the current discussion has gone well beyond an internalist examination.

Furthermore, we went to great lengths in Animal Models in Light of Evolution to acknowledge that animals have played a role in past discoveries and that basic research using animals can lead to discoveries yet much of the discussion here has revolved around this use. Yet, in this blog discussion LifeScientist and Dr Ringach have consistently avoided our intended internalist examination of the topic of prediction (or misrepresented or denied the facts) and attempted to discuss the historical use of animals (a controversial area on its own) or the relevance of using animals in basic research (an area where we both agree and disagree with LifeScientist and Dr Ringach). While such discussions are worthwhile, they avoid the main points we make in Animal Models in Light of Evolution and the position we take in general. The problem with discussing these issues prior to settling the prediction issue is that the defintion of prediction and the empirical data surrounding it inform all the other areas. One cannot examine the role of animals in history or their present role in basic research without first agreeing on the prediction issue.

Any attempt at having such a discussion without first defining terms and agreeing on data will (apparently) degenerate into name-calling (e.g., mindless and silly) and other ad hominem attacks as well as ad miscordium and ad populum arguments.

Science has important features as explained by my coauthor Dr Shanks: Good science involves critical thinking about evidence, methods and the interpretation of data. Good science involves consideration of alternative hypotheses. Good science is open to public demonstration.

Some facts have become clear with this discussion.

1.     Claims are not the same as proof. Claims are easy to make but proofs are hard and require more space (that might be why books were invented).

2.     It is difficult if not impossible to counter every false claim. First, there is simply a time factor and second, even when claims, like the anesthesia claim of earlier blogs, are countered the opponent can simply switch to another claim and demand proof to counter it. While this has rhetorical advantages it is not the protocol of science and critical thought.

3.     Dr Ringach agreed to debate claims as they relate to prediction at UCLA and has now reneged on his word. Blogs are great but actually seeing the person making the claims gives the interested party more data with which to judge claims. The lights of an auditorium expose more than just the room. Richard Feynman was comfortable in auditoriums, in front of Congress, as well as explaining his research to individual nonscientists.

4.     We are going in circles.

As I stated in my introductory blog:

The Internet has been an outstanding educational resource. We wrote two books essentially before the Internet as we know it now and three since. The three latter books are much better, in part because of the facts and articles we could access via the World Wide Web. That having been said, science education is not conducive to learning via Internet. Many controversies can be studied using the Internet, for example creation versus evolution, the validity of complimentary and alternative medicine, and the use of animals in science. But in order to really understand the nitty gritty science behind all these subjects one needs to go back to the last century. One needs to read books . . . But there is another factor to evaluating claims of any kind and that is called critical thinking. Critical thinking is difficult to teach to oneself, but reading the material at the previous link (Wikipedia) and the material from the links provided there will help.

In my opinion, we have come to the point in this discussion where the reader is being told completely opposite things and these things cannot be settled by further blogging. Now is the time to read books and examine the issues for your self. AND, hopefully for those who have participated to take the discussion to a different forum in order to allow the reader to judge these claims in a different light.

In keeping with that, I again ask Dr Ringach and or LifeScientist and or Dr Gorski or Orac to participate in a Point-Counterpoint of the prediction issue in a peer review journal. In such journals, name-calling, ad hominems and other examples of fallacious reasoning are not allowed to cloud the issue; facts and data are the rule. How anyone can solemnly claim to take science seriously and to have the science on his side and yet refuse to take this to the scientific journals is beyond my comprehension. I am not alone in this position.

I will continue my blog on Opposing Views and I thank the people who have made Opposing Views possible. But until Dr Ringach agrees to a formal, moderated debate (complete with a panel of experts who can act as judges) on prediction at UCLA as he promised and until Dr Ringach and or LifeScientist and or Dr Gorski or Orac agree to participate, with me, in a Point-Counterpoint in the scientific peer-reviewed literature, I will no longer respond to their unsubstantiated claims on Opposing Views.


Bynum, W F, E J Browne, and Roy Porter. 1981. Dictionary of the History of Science: Princeton University Press.