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Biophilosophy: Analytic and Holistic Perspectives by R Sattler

By R Sattler

This ebook is an creation to biophilosophy, written essentially for the coed of biology, the working towards biologist, and the informed layperson. It doesn't presuppose technical wisdom in biology or philosophy. even though, it calls for a willingness to ascertain the main easy foundations of biology that are so usually taken without any consideration. in addition, it issues to the bottomlessness of those foundations, the secret of lifestyles, the Unnamable .,. i've got attempted to extra the attention that organic statements are in line with philosophical assumptions that are found in our minds even sooner than we input the laboratory. those assumptions, which regularly harbor robust commitments, are uncovered during the publication. i've got attempted to teach how they impact concrete biologĀ­ ical learn in addition to our own lifestyles and society. therefore, emphasis is put on the relationship among biophilosophy and organic learn at the one hand, and biophilosophy and the human at the other.

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Mohr 1977, lectures 11-14). "Empirical adequacy is a measure of the number of facts accounted for by the science, and the precision, detail, and predictive power whereby it provides its account" (Laszlo 1973, p. 388). In short, empirical adequacy refers to the agreement of facts and theory. , the more confirming facts and the less disconfirming facts we have, the greater is the empirical adequacy. "Integrative generality (G) is a measure of the 33 internal consistency, elegance, and neatness of the explanatory framework.

As is well known, the young silver salmon hatch in the streams of the Pacific northwest. They swim downstream to the ocean and fmally a certain percentage of them returns to exactly the same stream in which they were born. The problem is: how do they find their way back? By sight or by odor? If we test the visual hypothesis, we can make the following deduction: blindfolded salmon will not find their way back. In this case the deduction (or prediction) will have to be formulated in statistical terms, but that does not change the basic principle of testing.

According to this hypothesis, which states that all swans are white, we can deduce (predict) that the next swan that we shall encounter will be white. If that swan turns out to be white, we have an agreement of deduced and observed states of affairs and hence, according to the first postulate of validation, proof of the white swan hypothesis. It is, however, evident that one successful prediction cannot constitute proof of that hypothesis. Even if we had succeeded in making a thousand (or more) correct predictions, we could not be assured that the next swan we observe will also be white.

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