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 quotes, a naval example, an analogy to military strategy and tactics, and two competitive-chess quotes. Clearly, Jarrard is an American male.

Wilford [1992a] offers a disturbing insight into a scientific field that today is questioning its fundamentals. The discipline is anthropology, and many anthropologists wonder how much of the field will survive this self analysis unscathed. The trigger was an apparently innocuous discovery about the Maori legend of colonization of New Zealand, a legend that describes an heroic long-distance migration in seven great canoes. Much of the legend, anthropologists now think, arose from the imaginative interpretation of anthropologists. Yet significantly, the Maoris now believe the legend as part of their culture.

Can anthropologists hope to achieve an objective knowledge of any culture, if that culture’s perceptive and analytical processes are inescapably molded by a different culture? Are they, in seeking to describe a tradition, actually inventing and sometimes imposing one? If cultural traditions are continuously evolving due to internal and external forces, where does the scientist seek objective reality? Are the anthropologists alone in their plight?

Pitfalls of Subjectivity
“The nature of scientific method is such that one must suppress one’s hopes and wishes, and at some stages even one’s intuition. In fact the distrust of self takes the form of setting traps to expose one’s own fallacies.” [Baker, 1970] How can we reconcile the profound success of science with the conclusion that the perception process makes objectivity an unobtainable ideal? Apparently, science depends less on complete objectivity than most of us imagine. Perhaps we do use a biased balance to weigh and evaluate data. All balances are biased, but those who are aware of the limitations can use them effectively. To improve the accuracy of a balance, we must know its sources of error.

Pitfalls of subjectivity abound. We can find them in experimental designs, execution of experiments, data interpretations, and publications. Some can be avoided entirely; some can only be reduced.

Experimental Design
• ignoring relevant variables: Some variables are ignored because of sloppiness. For example, many experimental designs ignore instrument drift, even though its bias can be removed. Often, however, intentions are commendable but psychology intervenes.
 * 1) We tend to ignore those variables that we consider irrelevant, even if other scientists have suggested that these variables are significant.
 * 2) We ignore variables if we know of no way to remove them, because considering them forces us to admit that the experiment has ambiguities.
 * 3) If two variables may be responsible for an effect, we concentrate on the dominant one and ignore the other.
 * 4) If the influence of a dominant variable must be removed, we are likely to ignore ways of removing it completely. We unconsciously let it exert at least residual effects [Kuhn et al., 1988].