Introduction
Historically, since the Scopes trial in 1925, the legal debate over what to teach about origins in science school classrooms has centered on biblical creation versus evolution. With the string of defeats in the courtroom against creationism being given equal time with evolution, a newer form of opposition to evolution has arisen through the Intelligent Design (ID) movement.1 For many people who consider any type of opposition to evolution in science education a breach of “separation of church and state,” this newer intelligent design-evolution battle often translates to an interventionist God versus Darwinism, or yet another way of stating religion versus science. Within non-theist scientific forums, the strongest model presented for biological evolution is modern Darwinism (natural selection as modified with genetics) with no scientific role seen for intelligent design. In forums like Perspectives on Science and Christian Faith, the debate has focused more on philosophical issues such as whether there is (or should be) a role for intelligent design (different from naturalism) in scientific research or education.2
As a philosophical choice, intelligent design is at least as rational an explanation of origins as is Darwinian evolution.3 Further, although Darwinism is the most widely accepted model of evolution for scientific inquiry, Booher shows its foundations are secured more on mentally pleasing perceptions and semantic arguments than on observational and experimental data.4 No long term experiments have ever shown macro-evolution to occur naturally and other convincing evidence once anticipated has not been forthcoming. Paleontology has not produced the finely connected array of fossils that Darwin expected;5 biochemistry does not show homologous connections between species at the protein level;6 and probabilities rule against chance having produced the complexity needed for progressively higher functions in species.7
Intelligent design, on the other hand, can explain the complexity in biology through such things as the cosmological tuning for life beginning with the Big Bang in scientific terms. For example, Darwinian gradualism says nothing scientific about the thermodynamic interface of precursors to the origins of life, species, and the human mind. None of these origins is thermodynamically plausible from the energy available in speculated precursors.8 Estimations of the increases in complexity to create novelty from precursors can, however, be specified in terms of intelligent information.9
Yet Darwinism continues to be more acceptable to most scientists (including theists) than intelligent design as a model for origins science. The general perception is that Darwinism, even if bad science, is still science; whereas, intelligent design, even if highly logical, is still religion, not science.10 The difficulty of advancing intelligent design or creationism as an alternative to Darwinism (as science, not philosophy) cannot be overemphasized, so long as this perception exists not only within the scientific community at large, but among scientific theists as well.
Booher suggests that systems psychology may offer some fresh insight into this issue for scientific theists.11 If so it would be primarily in helping address the following needs: (1) the need for a practical understanding of the phenomenon for intelligent people to prefer a non-verified (even falsified) scientific hypothesis over a logical, highly plausible explanation for origins and (2) the need for a practical strategy to correct any psychological errors associated with this phenomenon. In order to begin to address these needs, we must first get out of the hopeless cycle of "evolution versus creation," and begin to assess the value of specific areas of scientific inquiry in advancing knowledge about origins; in other words to find a way to better assess the scientific confidence we can place on various scientific approaches and claims to answer questions about origins. In order to qualify as science, intelligent design must do more than find fault with Darwinism; it must suggest scientific research on questions that are distinct from those suggested by evolution. Further it must provide hypotheses that are capable of being verified (or falsified) with the scientific method as is already true with Darwinism.
This paper proposes we return to the strengths of the scientific method and assess origins science in specific terms for specific limited scientific issues, rather than continuing to put the vast majority of Christian intellectual resources into a winner-take-all-fashion that pits grand philosophical theories against one another other in a way that may actually be impeding scientific progress in defining origins.
Levels of Confidence
Perhaps one of the most important statements on the philosophy of science ever made by Carl Sagan was his declaration: “Not all scientific statements have equal weight.”12 Here and in his other writings Sagan recognized the scientific method as centermost in distinguishing the relative value of the numerous scientific pronouncements. To have high confidence in the truth of any particular statement, one needs to know to what degree some of the higher techniques of science, like hypothesis formulation, controlled experimentation, direct observation, repeatability, falsifiability were applied.
Scientific levels of confidence can discriminate among the findings of physicists. Today we can be very confident the earth is round and know its exact size. Before Columbus thinkers had erroneous theories about both shape and size. Leucippus and Democritus postulated atoms in the sixth century BC but not until the beginning of the twentieth century were we sure of the existence of atoms and certain elemental particles. We can be highly confident in knowing the structure of the genetic code and the existence of genes whereas knowledge when or how life began has very low scientific confidence. We also have relatively low confidence at our current state of knowledge in the truth of the GUT (Grand Unified Theory) or time of cosmological beginnings. That does not mean theories of low scientific confidence have been proven false. Eventually some or perhaps many of them may eventually be shown to be correct. But currently we are on solid ground in being as skeptical of such ideas as we wish.
While philosophers may debate on whether or not there is such a thing as “truth” or “certainty,” within science pragmatic tests for truth can be defined. A thing or event or process is more or less certain to the degree anyone in the world can repeatedly find it to be true when he or she take actions assuming it to be true. Every technological development that is successfully applied to everyday use is based on scientific principles that are true. Every time we turn on a light, or fly an airplane, or operate a computer, we personally verify the underlying physics principles that were used in developing that technology. On the other hand, ideas science has shown to be absolutely false, such as perpetual motion machines, spontaneous generation, or a flat earth are to be discarded entirely. They may have been valid hypotheses for investigation at one time, but every scientific experiment and every observation ever made on these topics conclusively show they are not only inconsistent with proven principles but have no incontestable examples in their favor.
There are, of course, many ideas that lie along the scale from absolutely false to completely certain. These are potential candidates for scientific investigation in the quest to acquire certain knowledge. But not all questions or ideas are amenable to scientific verification. In fact, most are not. According to Mortimer Adler, science must remain silent on questions raised in moral or political philosophy, as well as matters covered through philosophical analysis. Moreover, he would say, science has no business in any of the metaphysics (those questions raised about nature, mind, and theology which cannot be answered by empirical investigation).13 Fortunately there are methods outside the scientific realm that can give us greater or less confidence in their truth. Philosophers and theologians can apply these other methods. There can be a filtering back and forth of method and thought among the three domains, but the fundamental strengths of each in determining certainty of statements are unique. In philosophy it is logical discourse; in theology it is the revealed word; in science it is the scientific method of investigation. Of the three, only science has shown truth with the confidence that everyone accepts. Because of this there is a tendency to err in thinking all statements of science on any topic have greater weight than non-scientific statements. But as Carl Sagan has correctly said, not all scientific statements have equal weight. Further, science cannot make valid statements about all things of human interest. Mortimer Adler argues that even such a question of what the subatomic world is like (determinate or indeterminate) is not answered and routinely claimed the domain of quantum physics is answerable, if at all, only by philosophy.14
Scientific Confidence Model 15
Based on the considerations raised above, can the scientific community make greater strides in assuring real progress is made in the knowledge of origins? What follows is a pragmatic proposal for a three-stage scientific confidence model that is applicable to all science, not just origins science. It is origins science in particular however that suggests the need for such a model. By evaluating origins science using the model for general science, it is relatively easy to see the various strengths and weaknesses of specific claims of origins scientists. To the degree any particular study or idea on origins can be made to fit the model a relative scale of confidence can be attributed to the study or idea. For example, even if a study is well executed, confidence can only reach the maximum allowable by the category under which it fits. Poorly executed studies, of course, should have their results discarded regardless of the category.
The model shown in Figure 1 comprises three types of activities (stages) arranged in order from left to right for increasing potential to establish scientific confidence.
Processing Rules:
1. Ideas can initially appear in any stage, move between stages or skip stages in either direction. To be investigated in any particular stage, however, they must meet the minimal criteria for the stage. For example, an idea may start in stage 2 or 3 from unexpected test results, but if it cannot be tested it must move back to stage 1. This example is represented graphically in Figure 1 by the arrows labeled III? where one arrow is an output from stage III and others are feedback inputs to stages I and II. Similarly questions from stage II can feedback to stage I. (see arrows labeled II?).
2. Verifiable hypotheses must be formulated in order to advance an idea beyond stage 1. As shown in Figure 1 hypotheses (see arrows I. Hyp; II. Hyp.) are shown feeding subsequent stages. Hypotheses can also be generated and tested within stages. Questions may feedback, but hypotheses are attempts to progress to higher levels of confidence.
3. Independent findings may strengthen confidence within a stage of examination but do not in themselves increase confidence beyond the stage of examination. For example, great coherence of logic from numerous independent concepts in stage 1 does not raise scientific confidence to the level of subsequent stages or even allow the ideas to be investigated at the higher stages if no testable hypotheses are generated.
4. The stage of examination does not necessarily reflect the level of scientific confidence that will ultimately be determined. For example, an idea like the flat earth can qualify for stage 3 but upon falsification should disappear entirely as a scientific question.
Figure 1. Scientific Confidence Model. The confidence that can be attributed to any idea capable of being investigated by the scientific method varies from low to high. The level of confidence can increase depending on the stage of scientific activity; whether I. Creativity, II. Analytical Representation; or III. Reality Verification. Scientific creativity is most distinct from philosophy when the mental activity results in scientific hypotheses. Analytical representation advance confidence through models and simulations. Reality verification is accomplished with descriptive and experimental science.
Stage I: Creativity.
This first stage of scientific activity is where ideas are generated and fleshed out by thinking. Rational thought is certainly involved in putting structure to an idea, but it is not necessary for generation of all ideas or even most discoveries. Concepts that come from inspiration, imagination, intuition, and instinct (an sometimes, just plain luck) are not unusual at this stage. In fact W.I.B. Beveridge in his now classic book on The Art of Scientific Investigation says “discoveries originate more often from unexpected experimental results or observations, or from intuitions, than directly from logical thought.”16 It is activity at this stage that often motivates scientists to be scientists, where discovery planned or accidental is always possible, such that imagining it happening, even vicariously, excites and stimulates to such a degree that it is difficult to compare with other human motivators.
This stage is closest to the other intellectual domains of philosophy and theology. For origins science, ideas of naturalism and intelligent design may be stimulated from philosophy. From theology may come ideas of a pantheistic or monotheistic cause for the universe. As ideas become more mature, such critical scientific methodologies as hypothesis formulation and prediction of observations become applicable. An idea never leaves this stage with a confidence higher than that from philosophy, no matter how much thought has gone into it, or how great the consensus gained from other thinkers, until a hypothesis or a prediction is made concerning it. Only then can the idea be tested at the other stages. Even an accidental discovery that came about by pure luck or a speculative urge that suggested where to look, say at finding a new star or new cure for cancer, must be verified by tests in the latter activities. One cannot know whether a new star or a new cure has been found without comparing with what is already known about astronomy and medicine. If a testable hypothesis is not or cannot be formed and the idea is not discarded on logical grounds, then the idea is doomed to continually circulate back and forth between philosophy and science at its lowest confidence level. Consensus on speculations and correlation with other suggestions, even highly mathematical ones, do not advance the idea significantly toward high scientific confidence.
Stage II: Analytical Representation.
The special art of scientific investigation begins at this stage. The two types of investigation that collect empirical data in a way that distinguishes them from the first stage of science and all of philosophy are the empirical sciences and historical research. Pure historical research of natural history (which performs no experiments) is technically not within the domain of science,17 but an exception is made for origins science where the overlap in modes of investigation is great and contributions can be easily made from one to the other.
Scientific thinking employs rational thought to a very high degree in the analytical stage. Beveridge completes his statement above on the importance of intuition and luck in discoveries with emphasis on the role of reason being “the principle agent in most aspects of research and the guide to most of our actions.”18 On the road toward proof, he says: “It [reason] is the main tool in formulating hypotheses, in judging the correctness of ideas conjured up by imagination and intuition, in planning experiments and in deciding what observations to make, in assessing the evidence and interpreting new facts, in making generalizations and finally in finding extensions and applications of a discovery.”19
One novel characteristic of the middle stage of scientific confidence development is that it is here where the investigator makes models and simulations of the reality he or she wishes to better understand. In making analytical models and simulations, the investigator often needs to consider a very large number of factors in combination. Hunches and imagination still play a role in identifying potential variables to study but precision and completeness are necessary to successfully model complex processes. One may be able to find large factors that account for most of the variance in a process but this requires correlational methodology to show which factors are important and which are not. The invention of the computer has allowed far more variables to be included and allows greater ability to verify accuracy of models. For example, if a computer model can be developed which considers all the major factors assumed to be operating in a process like speciation, it could be useful in testing assumed evolutionary effects of Darwinian natural selection.
Scientific rigor increases significantly during stage II. Hypothesis formulation and predictions are routine. For many questions, repeatability and falsifiability are features that can now be applied. Any mathematical models or simulations employed are presented in such a way as to have their assumptions carefully scrutinized. Simulations need to closely replicate a possible prebiological environment if their results are to increase confidence that this is how life started. Also independent methods of verifying assumptions are part of the scientific method at this stage. It is difficult to advance the evolutionary concepts of population biology and cosmology beyond stage I if they depend solely upon mathematical speculations without independent corroboration. When theistic scientists develop simulations or models that meet the criteria of stage II, they too need to present independent methods of verification. For example when creationist Gerald Aardsma wished to verify his model for radiometric time dating based on a catastrophic flood model, he used the independent method of tree rings for correlation. Since the result was highly correlated, he provided a model that was of greater scientific confidence than those based on stage I speculations.20
Although greater scientific confidence can be established at the analytical stage than the creativity one, the situation can arise where more than one model is offered to explain the same process. This is particularly troublesome, as in origins science, where the underlying assumptions differ considerably. As with developing a model originally, the best criterion for selection between competing models is reality verification by controlled experiment or direct observation. In the development of flight simulators for pilots, for example, human performance can be tested in the real world and the simulation adjusted until fidelity is excellent. For models or simulations of origins, this kind of verification is not possible. The next best option is selecting the model that best correlates with other known laws of reality, as for example, the laws of thermodynamics, genetics, or gravity.
Stage III: Reality Verification.
Two categories of scientific activity are included in the third stage. Both are necessary and valid for operations at the highest confidence level since both can help prove assumptions about reality. First is the more routine work of descriptive science. Activities like species classification and world mapping are not only exact but essential science. Where would astronomy or geography be were it not for the mappers of the stars and maps of the early explorers? Today geology may be finding a return to greater descriptive activity by including catastrophe.
The other category of activity for stage III includes those observations and experiments that have the primary purpose of verifying theoretical predictions. The distinguishing feature in both categories is that the scientist actually sees (directly with the senses or with instruments) something that can be recorded for others to verify independently.
Observation in the last stage of scientific confidence development provides something more than the formal mathematical confidence that can accrue in the other stages. Although pure mathematics is a very exact discipline, it is still a tool, no better no worse at providing answers to philosophical questions than the mind that employs it. Mathematics allows the rejection of inconsistent ideas and the forming of very precise hypotheses in stage I. Mathematics allows the rejection of spurious variables and the formulation of very exact and complicated models and simulations in stage II. But predictions and representational models of reality are not proven by mathematical operations. Once analytical representations are proven by observation, they can be reliably used thereafter as valid under a similar set of circumstances and assumptions. But until the mathematical nicety is verified by sky, field or laboratory observation, its underlying assumptions are still considered on weak foundation.
The highest stage of confidence is established by reality testing. In the case of theories, confirmation depends primarily on controlled experiment and direct observation of predictions. Not every idea generated or model compiled can be subjected to such rigor. But to the degree it is and found successful, not just once, but over and over again, great scientific confidence can be assigned to the idea as a definite increase in knowledge. Grand ideas like electromagnetics, genetics, thermodynamics, and gravity have repetitively met the criteria for “truth” at the highest level we know. Conversely, to date, no grand ideas or models on the origins of the universe, life, species, or appearance of the human mind have successfully exited stage III, not even once.
Application of Model to Origins Science
In order to apply the scientific confidence model to current issues in origins, it is helpful to distinguish grand ideas (like evolution and special creation) from ideas of limited extent (like micro and macro natural selection). To establish grand ideas with high scientific confidence requires extensive experimental verification from many different avenues. Ideas of limited extent however, may progress more easily. Also verification of several ideas of limited extent can increase confidence within the stage of examination. It is very tempting, however, to attempt to advance to higher stages purely on the basis of adding up disparate ideas of limited extent. For Darwinism many forms of evidence can be drawn from different fields, say biochemical, geological, mathematical, etc., and from this argue that taken in combination the evidence is so extensive that Darwinism is entitled to the scientific status that might be given to any other verified Grand idea of science. In philosophy this type of argument is likened to believing that having many buckets each with holes in them will hold more water than just one bucket with a hole. Rule 3 above provides a critical limitation on how far scientific confidence can advance from disparate forms of evidence
Another important distinction is Scientific Confidence Potential versus established Scientific Confidence. Rule 4 above was specified in order to handle this distinction. This is illustrated in Tables 1 and 2 where the categories of Grand and Limited ideas are classified for their highest potential level and their currently established confidence level.
Table 1 illustrates how the author would judge some grand ideas using the Scientific Confidence Model. [Note: When models appear plausible, but not yet developed, they are indicated by ?]. Creation and Evolution (1 and 2) are so broad that they do not have the potential to be examined even at stage I. That is, there is no testable hypothesis that can be stated to test either Grand Idea when stated so broadly. As we become more specific, with scientific ideas that infer a creator (3,4,5) or which infer purpose in nature (6) it is possible to form testable hypotheses which if successful might extend to still further verification through models. This has been done with Intelligent Design for a scientific theory of origin of life.21 With the notable exception of Intelligent Design all of the grand ideas on origins that currently compete with Darwin or Lamarck are stuck in stage I. That is, scientific hypotheses may have been formed conceptually, but not well enough to be tested even as models.
It is interesting that both Darwinism and Lamarckism (7,8) have the potential for higher scientific confidence than any of the grand ideas requiring a higher intelligence or purpose. However tests at the highest confidence level have routinely shown neither idea to be true (at least for macro evolution; which is essential for a grand idea). In fact, one might consider these ideas to have been falsified by experiment; therefore should be eliminated. They might have some value on a more limited scale, but not as grand theories that naturalistically explain origins.
Grand ideas like genetics, thermodynamics, gravity, and electromagnetics (10, 11, 12,13) that are neutral toward origins not only had the highest potential for confidence, but are now established at the highest scientific confidence level. Only Intelligent Design has reached the scientific confidence level stage II. The models and simulations of Intelligent Design support the hypothesis that some form of intelligence scientifically explains the origin of life. Considering that Darwinism is either at stage I or can be eliminated as a grand theory of origins, Intelligent Design remains as the best scientific explanation of the origin of life.22
Ideas like Big Bang (14) Age of the Earth (15) and Grand Unified Theory (16) that do have evolutionary implications are not capable of being verified at the highest level. They do however have the potential for model verification, and in the case of Big Bang and Age of the Earth have been independently corroborated with different models.
The last two examples, Flat Earth (17) and Sun Revolves Around The Earth (18) are illustrations of scientific theories that at one time had potential for examination at the highest level; but (being completely falsified with every known tool to science) are now eliminated.
This model shows graphically why Darwinism might initially be viewed favorably over Intelligent Design as a scientific theory of origins. Potentially it ranks with genetics and gravity that have been verified at the highest level. But that is only half of the picture. When we look at theories that have been tested at the highest level, Darwinism actually ranks closer to Flat Earth. As a grand idea it has failed all scientific tests at both the analytical and reality verification stages.23 The danger of a theory being tested at the highest level is that it can fail, making it lower in confidence than theories still at the analytical verification stage.
The confidence model is encouraging for intelligent design because it shows the potential for actual scientific progress in origins science is currently higher than Darwinism. [This is true for two reasons. 1. Darwinism has failed higher level tests, 2. Intelligent design has passed higher level tests.]. Intelligent design scientific researchers have successfully specified testable models and simulations clearly distinct from Darwinian models.
Since all grand ideas on origins other than Intelligent Design seem to be stuck at the lowest level of scientific confidence, a different tact appears necessary for progress of the other competitors. One suggestion is to attend to the ideas of limited extent with concentration on moving ideas from the creativity level to the analytical representation level. Some ideas of limited extent may even be testable at the reality verification level. Intelligent Design has already accomplished some experiments at stage III24. A number of limited scientific ideas are suggested in Table 2. As with the grand ideas, the scoring indicates the author’s judgment from his personal review. The reader may find considerable disagreement with these classifications, but the primary purpose of both tables is to illustrate how the scientific confidence model may be exercised in developing one’s personal confidence in scientific statements. It would appear that experts in the various fields could use the model to build greater consensus on origins issues and scientific relevance, with greater independence from philosophical or religious preferences.
Implications for Research and Education
Many of the limited scientific ideas regarding origins and biological change have suggested hypotheses that have either been verified or rejected in the reality verification activities. From evolution the idea of natural selection for species variation has been demonstrated in micro and population biology. But many other ideas of evolutionary origins have been falsified. Experiments have shown no spontaneous generation. Lamarckian hypotheses have been falsified in animals. Experiments have consistently shown little encouragement that people will be able to create life or urge organisms along any theoretical evolutionary path. From theism species are found classifiable and stable, but no predictions are made on the bounds of variation within a “kind.”
Currently Darwinism is the only evolutionary idea that still meets the requirement for hypothesis formulation stated in such a way to be capable of verification (or falsification). This has allowed it access to the more formal activities of the analytical and reality verification stages. Intelligent design as a grand scheme cannot reach the reality verification stage because a super intelligence cannot be evoked at will. It can however conduct experiments that give results that support intelligent design over Darwinism as best explanation of results. Most importantly however, intelligent design has met the criteria for advancing in the confidence process. They have testable hypotheses and predictions that allow testing at the analytical representation level. Moreover this testing has been done successfully. This shows Intelligent Design is fully scientific since it is capable of generating unique scientific hypotheses and models capable of corroboration.
Origins Research
One example uniquely suggested by intelligent design is research to define species. To distinguish itself from Darwinism, one theory of intelligent design sets limits to the amount of variation from natural selection and other random change mechanisms. It can ask research questions therefore on the limits of change that exist in species and can search for a more exact biological definition of what a species is.25 Another example is described by Gordon Mills who offers a unique theory of theistic evolution. His view is that “in the history of the origin and development of living organisms, at various levels of organization, there has been a continuing provision of new genetic information by an intelligent cause.”26 The macroevolutionary fossil trail essentially documents the “provision of new genetic information.” Mills’ view allows for both intelligent design and evolutionary chance to have operated in the past. Especially important for theistic science is that Mills’ theory suggests a positive approach to scientific research that is not bound to the naturalistic model. For example, he is not required to assume initial simplicity. “An intelligent cause could have provided genetic information for whatever degree of complexity that was necessary.”27 Consequently in molecular evolution he would not search for simpler structures of enzymes, membranes or genetic codes to better understand the fundamental life processes. Rather he would start by trying to understand aspects of the complexity preexisting each evolutionary change (for example, complex developmental genes) and then search not only for how the developmental genes could be switched on and off to effect changes in form, but also look for some new genetic information to account for each major evolutionary change.28
The systems approach to origins science offers many research opportunities, from the biochemical level, where the function and structure of precursor and novel systems can be defined in detail, through the specification of interfaces between such systems using information models,29 all the way up to models for integration of the sciences. All such models need to depart from solely mathematical speculations and move toward the specificity and confirmation which comes from corroboration with actual biological and physical systems. This will allow the models to progress into the analytical representation levels. For the integration of science fields based on intelligent design, a principal challenge will be to define interfaces between fields in such a way that they can be connected by information links that speak intelligibly with one another.
Origins Education
The scientific confidence model suggests science could best serve public education initially by acknowledging a generally low confidence level for almost all of its statements on biological origins. Even most analytical representation methods that could at least give moderate confidence of what happened in prehistory are poorly constructed, primarily ad hoc rather than predictive. Both private and public education school boards might be advised to search for ways to favor instruction in the scientific method over promoting scientific “enthusiasm.” Origins science can provide some very good examples of how the scientific approach can increase confidence in what we know and what we do not. Also, the history of origins science has numerous examples to help the student distinguish scientific observation from scientific interpretation. Origins science can illustrate well how a scientific contribution can be independent of the scientist’s philosophical or religious interpretation. Present day taxonomic classification was started by a creationist, Linnaeus, to show biblical “kinds;” later appropriated by Darwinists to show evolution; and adopted today by cladists who reject Darwinism.
The confidence model is silent on recommendations on what the science teacher should be required to teach. The model would support, however, those who resist attempts to constrain educators from teaching science to the best of their ability and understanding. This can be best appreciated in a past National Science Teachers Association position statement on the “Teaching of Evolution,” in which it recommends that “Science textbooks shall emphasize evolution as a unifying concept”30 and would not permit minority scientific views such as “so-called intelligent design.” The NTSA position would not even tolerate “arguments against evolution.” Moreover evolution would be Darwinian evolution since it would not allow the concept of “abrupt appearance.” Many of the topics discussed in this article illustrate the short sightedness of such an approach. As we have seen, both Darwinism and Intelligent Design have some explanatory value for science. Neither provides scientific confidence at the level of gravity or genetics. Non-Darwinian scientific models can, however, help teach the benefits of properly applying the scientific method to acquire a high level of scientific confidence in the findings of scientists. It is far better for the progress of science that the student understand how to discriminate the speculations of scientists (even if held by a majority) which give low levels of confidence from those proven by scientific investigation (which can have high scientific confidence even when demonstrated by a minority).
ENDNOTES
1. For a good example of the arguments for Intelligent Design being included in public science education see: John Angus Campbell and Stephen Meyer (eds.) Darwinism, Design, and Public Education (East Lansing, MI: Michigan State University Press, 2003). For a good presentation of the concerns that Intelligent Design is primarily religion see: Barbara Forrest and Paul R. Gross, Creationism's Trojan Horse: The Wedge of Intelligent Design (New York: Oxford University Press, 2004).
2. See for example, "Dialogue III: Intelligent Design and Naturalism," among James Madden, Mark Discher, and Howard J. Van Till, Perspectives on Science and Christian Faith 56, no. 4, (2004): 286-98.
3. See for example, Moreland, J.P. (Ed.) 1994, The Creation Hypothesis, Intervarsity Press, Downer’s Grove, Ill.; Jon Buell and Virginia Hearn (Eds.) 1994, Darwinism: Science or Philosophy? Foundation for Thought and Ethics, Richardson, Texas; Mere Creation: Conference on Design and Origins; Biola University, November 14-17, 1996; Dembski, W.A. “Intelligent Design as a Theory of Information,” Perspectives on Science and Christian Faith, September 1997, 49(3), pp. 180-190; and Meyer, Stephen, Signature in the Cell, New York:HarperOne; 2009.
4. Booher, H. R., 0rigins, Icons, and Illusions: The Science and Psychology of Creation and Evolution (Warren H. Green, Inc. St. Louis, MO. 1998). See especially Chapters 3-8 and 15-16.
5. The actual status of discovered transitional fossils is so small that the inference of Darwinian gradualism is no longer held by paleontologists. Paleontologist Kurt Wise states “the total list of transitional forms is very small ... compared to the total number of mosaic forms.”(in J. P. Moreland, (Ed.) 1994 The Creation Hypothesis, p. 227). Similar comments can be found throughout the paleontology literature. See, for example, David Kitts, “Paleontology and Evolutionary Theory,” Evolution, (Vol. 28, Sept. 1974 p 467) who states “Despite the bright promise that paleontology provides a means of ‘seeing’ evolution, it has presented some nasty difficulties for evolutionists the most notorious of which is the presence of ‘gaps’ in the fossil record. Evolution requires intermediate forms between species and paleontology does not provide them. The gaps must therefore be a contingent feature of the record.”
6. Behe, M. 1996 Darwin’s Black Box: Regnery; Behe, M. 1994, “Experimental Support for Regarding Functional Classes of Proteins to be Functionally Isolated from Each Other,” in Jon Buell and Virginia Hearn (Eds.) Darwinism: Science or Philosophy? Foundation for Thought and Ethics, Richardson, Texas; Denton, M.1986 Evolution: A Theory in Crisis, Adler and Adler.
7. Ambrose, E. J., 1982 The Nature and Origin of the Biological World, New York: Halsted Press; Yockey, Hubert P., 1989, The Mathematical Foundations of Molecular Biology, New York: Cambridge Press; Dembski, William 1995, “The Design Inference: Eliminating Chance Thorough Small Probabilities,” Technical Monograph. Copy available through Foundation for Thought and Ethics, Richardson, Texas.
8. Booher, H. R., op. cit., note 3. See discussion on thermodynamics and information theory in Chapter 12: “Reversing Time’s Arrow” pp. 224-247).
9. Bradley, W.L. and Thaxton, C. B. 1994, “Information and The Origin of Life,” in J.P. Moreland, The Creation Hypothesis; op. cit. note 2; pp. 173-210; and Meyer (op. cit., note 3)
10. See for example, typical comments of members of the American Scientific Affiliation in Perspectives on Science and Christian Faith. William Hasker (1992, Vol. 44 (3) pp. 150-162) while not opposed to theistic interpretations of the evidence for evolution is critical of Alvin Plantinga’s proposal for a theistic science, being dubious about the benefits to either Christianity or natural science. Raymond Grizzle (ibid, p.175) notes “all of modern science, not just biological evolutionary theory, by definition, excludes God... its descriptions are limited to the observable natural world."
11. Booher, H.R, “Systems Psychology and Origins Science,” Life After Materialism Conference, Biola University, December 2-5, 1999.
12. Sagan, Carl, 1977. Scientists Confront Velikovsky, New York: Norton, p. 59.
13. Adler, Mortimer J.1992. The Four Dimensions of Philosophy, New York: Macmillan, pp. 75-77.
14. Adler, Mortimer J. 1990. Truth in Religion, New York: Macmillan, p. 100.
15. Booher, H.R., op. cit., note 4, pp. 318-325.
16. Beveridge, W.I.B., 1957. The Art of Scientific Investigation, New York: Vintage (3rd Edition) p. 122.
17. Adler, op. cit., note 12, p 15.
18. Beveridge, op. cit., note 15, p. 122.
19. Ibid. pp. 122-123.
20. Aardsma, Gerald E., 1991. Radiocarbon and the Genesis Flood, Institute for Creation Research, El Cajon, CA.
21. Meyer, S. op. cit. note 3.
22. Ibid.
23. Darwinism could be proven at the reality verification stage if three forms of evidence were produced. These are (1) experimentally producing the evolution of new species; (2) discovering continuous connections between the species in the fossil record; and (3) mapping detailed biochemical connections between the species. No one disputes (1) has not been shown and is no longer tried. Darwinists claim progress in (2) but the record is too poor to be convincing. Biochemists Denton and Behe (op. cit., note 6) have shown that (3) does not exist. Additionally Behe (op. cit., note 6) and Meyer (op. cit., note 3) have also shown that no detailed analyses exist to show how natural selection could produce an increase in biological complexity. No Darwinist has ever built a detailed model down to the biochemical level connecting a precursor system to a supposed evolved system.
24. Meyer, S. op.cit. note 3
25. Davis, Percival and Kenyon, Dean H. 1993. Of Pandas and People, Dallas, Texas: Haughton Publishing Co., p. 85.
26. Mills, Gordon C. June 1995. “A Theory of Theistic Evolution as an Alternative to the Naturalistic Theory,” Perspectives on Science and Christian Faith, Vol. 47 (2), p. 121.
27. Mills, Gordon C. June 1995. “Theistic Evolution: A Design Theory at the Level of Genetic Information, Christian Scholar’s Review, pp. 1-12, p. 10.
28. Mills’ theory covers such possibilities as a.) rapid diversity of species (as might follow mass extinctions); b.) macroevolutionary events requiring a number of new genes and control factors; and c.) the dormant retention of genetic information until needed again hundreds, thousands, or possibly millions of years later. (Mills, ibid., p.115.)
29. It would appear some combination of Dembski’s (op. cit. notes 3 and 7); Bradley and Thaxton’s (op. cit., note 9); Behe’s (op. cit. note 6); and Meyer’s (op.cit., note 3) research on information theory, thermodynamics, and living systems specification could be used to map out systems research on interfaces between precursor and novel living systems.
30. “An NSTA Position Statement on The Teaching of Evolution,” 1997, National Science Teachers Association Arlington, VA.