Chapter IV – Philosophy of Science Topics

The preceding chapters have offered generic sketches of the principal twentieth-century philosophies of science, namely romanticism, positivism and pragmatism. And they have discussed the elements of the contemporary pragmatist philosophy of language for science, namely the object language and metalanguage perspectives, the synchronic and diachronic views, and the syntactical, semantical, ontological and pragmatic dimensions of language.

Finally at the expense of some repetition this chapter integrates those discussions into the four functional topics briefly examined in the overview chapter, namely the institutionalized aim of basic science, scientific discovery, scientific criticism, and scientific explanation.


4.01 Institutionalized Aim of Science

Over the last three hundred years empirical science has evolved into a social institution with its own distinctive and autonomous professional subculture of shared views and values. The institutionalized aim of science is the cultural value system that regulates the scientist’s performance of basic research. Idiosyncratic motivations of individual scientists are of less interest to philosophers of science, except when such idiosyncrasies have initiated an institutional change.

The literature of philosophy of science offers a variety of proposals for the aim of science. The three modern philosophies of science mentioned above set forth different philosophies of language, which influence their different concepts of all four of the functional topics.


4.02 Positivist Aim

The positivists proposed a foundational agenda. Early positivists such as Ernst Mach initially proposed that science should aim for firm objective foundations by relying exclusively on observation and on empirical generalizations that summarize individual observations. Theories were deemed temporary expedients and viewed as less than truly scientific.

After the acceptance of Einstein’s relativity theory by physicists, the later “neopositivist” philosophers acknowledged the essential role that hypothetical theory must have in the aim of science. Between the World Wars the neopositivist Rudolf Carnap and his fellow members of the Vienna Circle group attempted to justify the role of theories in science by relating the theoretical terms in the theories to the observation terms that they believed are a foundational reduction base.

These neopositivists were also called “logical positivists”, because they attempted to use the symbolic logic developed by Bertrand Russell and Alfred N. Whitehead, in order to accomplish the logical reduction. These neopositivists fantasized that the Russellian symbolic logic could serve philosophy as mathematics serves physics. In fact the Russellian truth-functional logic does not capture the hypothetical logic of empirical testing in science, and is no longer seriously considered by philosophers of science.

The neopositivist agenda was statements of these philosophers’ aim rather than the aim for science itself. Scientists did not use symbolic logic or seek any logical reduction for theoretical terms. The decline and eclipse of positivism was in no small part due to the disconnect between the philosophy and the practices of scientists.


4.03 Romantic Aim

The romantics have a subjectivist social-psychological reductionist agenda for the social sciences. This is a statement of the aim of social sciences that is embraced and enforced by many social scientists. Both romantic philosophers and romantic scientists maintain that these sciences of culture differ fundamentally in their aim from the sciences of nature. They view the aim of the social sciences as the development of explanations in terms of subjective social-psychological motives, in order to explain observed social-interaction in terms of purposeful human action in society.

Some romantics call this type of explanation “interpretative understanding” and others call it “substantive reasoning”. Using this concept of the aim of science they often say that an explanation must “make sense” to the social scientist due to the scientist’s personal experiences, especially when he is a participant in the same culture as the social members he is investigating.

Examples of these romantics are sociologists like Talcott Parsons and his followers, who advocate variations on the philosophy of the sociologist Max Weber, in which this vicarious understanding called “verstehen” is a criterion for criticism that trumps empirical evidence. This criterion has severely retarded the evolution of sociology into a modern empirical science in the twentieth century.

The economist Trygve Haavelmo and the neoclassical econometricians supply another example. They do not reject the aim of prediction and policy formulation using econometric models, but nonetheless subordinate the selection of “explanatory” variables in their econometric models to the description of subjective motives set forth in the maximizing rationality postulates that economists heroically impute to the participants in economic activities.


4.04 More Recent Ideas

Most of the twentieth-century post-positivist proposals for the aim of science arise from examination of important episodes in the history of the natural sciences rather than from the speculations and agendas of philosophers.

Albert Einstein’s idea was influenced by reflection on his relativity theory for his concept of the aim of science, which he set forth as his”programmatic aim of all physics” stated in his “Reply to Criticisms” in Schilpp’s Albert Einstein. The aim is the comprehension as complete as possible of the connections among sense impressions in their totality by the use of a minimum of primary concepts and relations. Its achievement is the representation of the multitude of concepts and theorems close to experience as theorems logically derived from and belonging to a basis, as nar¬row as possible, of axioms and fundamental concepts, which themselves can be chosen freely. Thus the aim of science is the logical unity of the world picture, a coherence agenda. He found statistical quantum theory to be incomplete according to his aim.

Thomas Kuhn, reflecting on the development of the Copernican heliocentric theory in his The Copernican Revolution: Planetary Astronomy in the Development of Western Thought and his Structure of Scientific Revolutions assigned institutional status to the prevailing theory, which he called the “consensus paradigm”. He proposed that small incremental changes extending the consensus paradigm define the institutionalized aim of science, which he called “normal science”, and that scientists neither desire nor aim consciously to produce revolutionary new theories, which he called “extraordinary science.” Kuhn therefore defines scientific revolutions as institutional changes in science.

Karl Popper was an early post-positivist philosopher of science and a critic of the romantics. Reflecting on the development of Einstein’s relativity theory in physics he proposed in his Logic of Scientific Discovery that the aim of science is to produce tested and nonfalsified theories having greater universality and information content than their predecessor theories addressing the same subject. The English-language title of his book notwithstanding Popper denies that discovery can be addressed by either logic or philosophy, but instead is the proper subject for psychology.

Norwood Russell Hanson reflecting on the development of quantum theory states in his Patterns of Discovery that inquiry in research science is directed to the discovery of new patterns in data for new explanatory hypotheses for deductive explanation. Following C.S. Peirce he calls this “abduction”, but does not propose any procedure for discovering the new patterns.

Paul Feyerabend also reflecting on the development of quantum theory proposed in his Against Method that each scientist has his own aim, and that anything institutional is a conformist impediment to the advancement of science. He said that historically successful science is literally anarchical, and he therefore proposed “revolution in permanence”.


4.05 Aim of Maximizing “Explanatory Coherence”

Paul Thagard developed his computerized cognitive system ECHO, an acronym meaning “Explanatory Coherence by Harmony Optimization”, in order to explore the operative criteria in theory choice by mechanically simulating noteworthy past episodes in the history of science.

James Cornman initially proposed the “best explanation” idea and called it “explanationism”. It refers to an explanation that aims to maximize explanatory coherence of one’s overall set of beliefs. Thagard’s system described in his Conceptual Revolutions simulated the realization of the aim of maximizing “explanatory coherence” by replicating various episodes of theory choice. He applied his system ECHO to several revolutionary episodes in the history of science including (1) Lavoisier’s oxygen theory of combustion, (2) Darwin’s theory of the evolution of species, (3) Copernicus’ heliocentric astronomical theory of the planets, (4) Newton’s theory of gravitation, and (5) Hess’ geological theory of plate tectonics.

In reviewing his historical simulations Thagard reports that ECHO found the criterion making the largest contribution historically to explanatory coherence in scientific revolutions is explanatory breadth – the preference for the theory that explains more evidence than its competitors. But he adds that the simplicity and the analogy criteria are also historically operative although less important. He maintains that the aim of maximizing explanatory coherence with these criteria yields the “best explanation”.


4.06 Contemporary Pragmatist Aim

The principles of the contemporary pragmatism including its philosophy of language evolved through the twentieth century beginning with the autobiographical writings of Werner Heisenberg, one of the central participants in the historic development of quantum theory. His philosophy of language was summarized above in Chapter II in the form of three central theses, which are not repeated here.

The institutionally regulated activities of research scientists may be described succinctly in the pragmatist statement of the aim of science, which the contemporary research scientist seeking success in his research may consciously employ as what some social scientists call a “rationality postulate”. Such a pragmatist rationality postulate may be expressed as follows: Scientists aim to construct explanations by developing theories that satisfy the most critically empirical tests that can be applied to the theories at the current time, and which are thereby regarded as scientific laws that function in scientific explanations. This statement is more elaborately explained in terms of the other functional topics as sequential steps in the development of explanations.

The institutionalized aim can also be expressed so as not to impute motives to the successful scientist, whose personal psychological motives may be quite idiosyncratic. Thus the contemporary pragmatist statement of the aim of science may be phrased in terms of the successful outcome instead of a conscious aim imputed to scientists:

The successful outcome of basic-science research is explanation, which is achieved by developing theories that satisfy the most critically empirical tests that can be applied to the theories at the current time, and which are thereby regarded as scientific laws that function as premises in deductive explanations of events.


4.07 Institutional Change

Institutional change in science must be distinguished from change within the institutional constraint defined by the aim of science. Philosophy of science is concerned both with changes within the institution of science and with historical changes of the institution itself. But institutional change can only be recognized retrospectively due to the distinctively historical uniqueness of each episode and also due to the need for emergent conventionality for new basic-research practices to become institutionalized.

In the history of science institutionally deviate practices, innovative instruments and unconventional concepts that yielded successful results were initially recognized and accepted by only a few scientists. As Feyerabend emphasized in his Against Method, in the history of science successful scientists have often broken the prevailing methodological rules. The successful departures eventually become conventionalized, and by the time they appear in reference manuals, encyclopedias and student textbooks the institutional change is complete.

But adequate understanding of successful departures from institutionalized basic research is elusive. Successful researchers have often failed to understand the reasons for their unconventional successes, and have formulated or accepted erroneous methodological ideas and philosophies of science to explain their successes. One of the most historically notorious such misunderstandings is Isaac Newton’s “hypotheses non fingo”, his denial that his law of gravitation is a hypothesis.

It is noteworthy that the contemporary pragmatist statement of the aim of science is itself a postulate in the sense of an empirical hypothesis. Therefore it is destined to be revised at some unforeseeable future time, when due to some future developmental episode, basic science practices are revised. Then some conventional practice deemed rational today will some time in the future likely be dismissed as superstition.


4.08 Philosophy’s Cultural Lag

As mentioned above adequate understanding of successful departures from institutionalized basic research is elusive even for philosophers. Not surprisingly there exists a time lag between the evolution of the institution of science and developments in philosophy of science, since the latter depends on the realization of the former. For example more than twenty-five years passed between Heisenberg’s philosophical reflections on the language of his uncertainty relations in quantum theory and the consequent emergence and ascendancy of the contemporary pragmatist philosophy of science in academic philosophy.

Due to the regulating role of the aim of science, any cultural evolution in science that involves a modification of the aim of science amounts to a greater or lesser institutional change, when it becomes conventionalized. Some such changes seem to occur with lengthy time lags due to such impediments as intellectual mediocrity, risk aversion or vested interests in the received conventional philosophical wisdom.


4.09 Cultural Lags among Sciences

Not only are there cultural lags between the practices of science and philosophy of science, there are also cultural lags among the several sciences. Philosophers of science have preferred to examine physics and astronomy, because historically these have been the most advanced sciences since the historic Scientific Revolution benchmarked with Copernicus. Many other sciences have tended to lag behind physics and astronomy with the newer social and behavioral sciences lagging farther behind than most of the natural sciences.

Naïve sociologists and economists are blithely self-confident in their ersatz philosophizing about basic social science research, often adopting prescriptions and proscriptions that contemporary philosophers of science view as erroneous, anachronistic and retarding. The result has been the emergence and survival of retarding philosophical superstitions in these lagging sciences, especially to the extent that they have looked to their own less successful histories to formulate their amateurish philosophies of science.

As mentioned above, sociologists and economists continue to enforce a romantic philosophy of science, because they believe that sociocultural sciences must have fundamentally different philosophies of science than the natural sciences. Similarly behaviorist psychologists continue to impose the positivist philosophy of science. On the contemporary pragmatist philosophy these sciences are institutionally retarded, because they erroneously impose prior semantical and ontological commitments as criteria for scientific criticism. Pragmatists recognize only the empirical criterion for scientific criticism.


4.10 Scientific Discovery

The functional topic after the aim of science is discovery. “Discovery” refers to the development of new theories, and is the first step toward realizing the aim of science.

The problem of scientific discovery for contemporary pragmatist philosophers of science is to describe and to proceduralize the development of universally quantified statements for empirical testing with nonfalsifying test outcomes.

Much has already been said in the above discussions of philosophy of scientific language about the pragmatic basis for the definition of theory language, about the semantic basis for the individuation of theories, and about state descriptions. That will not be repeated here. Of special interest in the present context is the mechanized development of new theories.


4.11 Discovery Systems

As a creative event, the development of an empirically successful theory has a reputation for mystery. In the "Introduction" to his Models of Discovery Nobel laureate Herbert Simon says that dense mists of romanticism and downright knownothingness generally have always surrounded the subject of scientific discovery and creativity. Therefore the most significant development addressing the problem of scientific discovery has been the relatively recent computerized discovery systems in computational philosophy of science. The discovery system explicitly describes the transition from an input language state description containing currently available information to an output language state description containing the newly generated and tested theories.

The discovery systems do not merely implement an inductivist strategy of searching for repetitions of individual instances, notwithstanding that statistical sampling theory is employed in some system designs. The system designs are mechanized procedural strategies that search for patterns in data or linguistic input information. They thus implement Hanson’s thesis in Patterns of Discovery that in a growing research discipline inquiry is the discovery of new patterns in data.

Every useful discovery system to date has contained procedures both for constructional theory creation and for critical theory evaluation. Theory creation introduces new language into the current state description to produce a new state description, while falsification eliminates language from the current state description to produce a new state description. Thus both theory development and theory testing enable a discovery system to offer a dynamic diachronic description of linguistic change in science.

The ultimate aim of the computational philosopher of science is to facilitate the advancement of contemporary sciences by participating in and contributing to the successful basic-research work of the scientist.


4.12 Types of Theory Development

In his Introduction to Metascience Hickey distinguished three types of theory development. They are theory extension, theory elaboration and theory revision.

Theory extension is the use of a currently tested and nonfalsified explanation to address a new scientific problem. The extension could be as simple as adding statements to make a general explanation more specific for the problem at hand.

A sophisticated strategy for theory extension is analogy. In his Computational Philosophy of Science Thagard developed a strategy for mechanized theory development, which he says consists in the patterning of a proposed solution to a new problem by analogy with an existing explanation for a different subject. Using his system design based on this strategy his discovery system called PI, an acronym for “Process of Induction”, reconstructed development of the theory of sound waves by analogy with the description of water waves. Since the input is an existing explanation for a different subject, the input state description does not consist of untested theories already proposed to solve the problem at hand.

In his Mental Leaps: Analogy in Creative Thought Thagard explains that analogy is a kind of nondeductive logic, which he calls “analogic”. It firstly involves the “source analogue”, which is the known domain that the investigator already understands in terms of familiar patterns, and secondly involves the “target analogue”, which is the unfamiliar domain that the investigator is trying to understand. Analogic is how the investigator understands the targeted domain by seeing it in terms of the source domain, and it involves a “mental leap”, because the two analogues may initially seem unrelated. But the act of making the analogy may reveal new connections between them.

It may be noted that if the output state description generated by the system is radically different from anything previously seen by the affected scientific profession, the members of the profession may experience the communication constraint with colleagues that is usually associated with a theory revision.

Theory elaboration is a correction of a currently falsified theory to create a new theory by the addition of new factors or variables that correct falsified universal statements and erroneous predictions. The correction is not merely ad hoc referencing individual exceptional cases, but rather changes universally quantified statements. Except perhaps for description of the additional correcting variable, the new theory usually has the same test design as the old theory that is the basis for elaboration

For example Gay-Lussac’s law for gasses could be elaborated into Boyle’s gas law by the introduction of a variable for the volume quantity and a constant coefficient for the particular gas. Similarly Friedman’s macroeconomic quantity theory might be elaborated into a Keynesian liquidity-preference function by the introduction of an interest rate, to account for the cyclicality manifest in an annual time series describing over several decades the calculated velocity parameter.

The BACON discovery system, named after the English philosopher Francis Bacon (1561-1626) who thought that scientific discovery can be routinized, is a set of successive and increasingly sophisticated discovery systems that make -quantitative empirical laws and theories. BACON was designed and implemented by Pat Langley in 1979 as the thesis for his Ph.D. dissertation written in the Carnegie-Mellon department of psychology under the direction of Herbert Simon. A description of the system is in Simon's Scientific Discovery: Computational Explorations of the Crea¬tive Processes.

The system uses Simon’s heuristic-search design concept, which may be construed as a sequential application of theory elaboration. Given sets of observation measurements for two or more variables, BACON searches for functional relations among the variables. BACON has simulated the discovery of several historically significant empirical laws including Boyle's law of gases, Kepler's third planetary law, Galileo's law of motion of objects on inclined planes, and Ohm's law of electrical current.

Theory revision is a reorganization of currently existing information to create a new theory. It might be undertaken after theory elaboration has failed to correct a previously falsified theory. The data source for the input state description for mechanized theory revision consists of the descriptive vocabulary from the currently untested theories addressing the problem at hand. The descriptive vocabulary from previously falsified theories may also be included as inputs to make an accumulative state description, because the vocabulary in rejected theories can be productively cannibalized for their scrap value. The new theory is most likely to be called revolutionary if the revision is great, because theory revision typically produces greater change to the current language state than theory elaboration.

In the early 1970’s Hickey tested his METAMODEL discovery system by synthesizing the Keynesian macroeconomic theory from variables and U.S. statistical data available prior to 1936, the publication year of Keynes’ General Theory of Employment, Interest and Money. The applicability of the METAMODEL for this theory revision is already known in retrospect by the fact that, as Nobel laureate econometrician Lawrence Klein said in his Keynesian Revolution, all the important parts of Keynes theory can be found in the works of one or another of his predecessors. Hickey’s METAMODEL discovery system is a combinatorial procedure for theory revision, a system design that Simon calls a “generate-and-test heuristic-search design”. It might be said that this system design implements Feyerabend’s principle of “theory proliferation” at electronic speed. The mechanized proliferation is a tsunami of options that the system constructs and tests empirically in its run.

Hickey also used his discovery system to develop a macrosociometric institutional model of the American national society with seventy-five years of historical time-series data. To the shock, chagrin and dismay of the academic sociologists the model was not a social-psychological theory. Due to their a priori ontological commitment to romanticism the communication constraint rendered them invincibly obdurate, and they furthermore exhibited a Luddite attitude toward mechanized theory development.


4.13 Examples of Successful Discovery Systems

Examples of some successful discovery systems that are in use include Sonquist’s AID system (1961), Hickey’s METAMODEL system (1976), and Litterman BVAR system (1980).

Sonquist developed his AID system as a doctoral dissertation at the University of Chicago. He described it as a discovery strategy in his Multivariate Model Building: Validation of a Search Strategy. The system has long been used at the University Of Michigan Survey Research Center. Now known as the CHAID system Sonquist’s discovery system is available commercially in SAS and SPSS statistical packages, and is by far the most widely used of all the discovery systems yet created.

Hickey was a graduate student at the University Of Notre Dame at South Bend, Indiana, but the philosophers have a reform-school culture and told him to get reformed or get out. He got out and then developed his METAMODEL discovery system at San Jose College in California. In the more than thirty years since Hickey first developed his system, he has applied his discovery system for economic analysis at Kraft Foods, Brown & Williamson Company, Quaker Oats Company, U.S. Steel Corporation, Allstate Insurance Company, TransUnion LLC, and the State of Indiana Department of Commerce.

Litterman developed his BVAR system as a doctoral dissertation at the University of Minnesota, and today economists at the Federal Reserve Bank of Minneapolis use his system for macroeconomic analysis.


4.14 Scientific Criticism

The functional topic after the aim of science and discovery is criticism. The philosophical literature on scientific criticism has little to say about the specifics of experimental design. Most often it pertains to the criteria for the acceptance or rejection of theories and the decidability of empirical testing.

The only criterion acknowledged by contemporary pragmatists is the empirical test. Contemporary pragmatists accept relativized semantics, ontological relativity and scientific realism. They therefore reject all prior ontological criteria for scientific criticism such as the romantics’ mentalism. The empirical criterion is what separates the empirical sciences from their origins in natural and moral philosophy, not to mention science-fiction literature. Whenever in the history of science there has been a conflict between the empirical criterion and any nonempirical criteria for the evaluation of new theories, eventually it is the empirical criterion that ultimately decides theory selection. The empirical criterion is the necessary condition for “progress” in basic science.

In the past philosophers and scientists had used their ontological preconceptions as criteria for the criticism of scientific theories including preconceptions about causality or specific causal factors. This presumption led them to reject out of hand new and empirically acceptable theories that did not conform to these ontological preconceptions. In his Against Method Feyerabend noted that the ontological preconceptions used by scientists to criticize new theories have often been earlier theories’ semantical and ontological claims elevated to criterion status.

The only criterion for scientific criticism acknowledged by contemporary pragmatists is the empirical criterion.


4.15 Logic of Empirical Testing

The universally quantified theory statements in an empirical test can be schematized as a nontruth-functional hypothetical-conditional statement, i.e., as a statement with the logical form “If A, then C.” The hypothetical-conditional statement itself represents the set of one or several universally quantified theory statements that describe the causal dependency of the phenomena described by “C” upon the phenomena described by “A”. The hypothetical-conditional statement is thus the theory-language context that contributes meaning parts to the complex semantics of the theory’s descriptive terms including the terms common to the theory and test design.

The antecedent “A” also includes the set of universally quantified statements of the test design that describe the initial conditions that must be realized for execution of an empirical test of the theory, and which also describe the test outcome independently of the theory’s predictions. These statements also contribute meaning parts to the complex semantics of the terms common to theory and test design, and do so independently of the theory’s claims. The universal logical quantification indicates that any execution of the experiment is but one of an indefinitely large number of possible test executions especially if the test is repeatable at will.

When the test is executed, the logical quantification of “A” is changed to particular quantification to describe the realized initial conditions in the individual test execution, and it is always presumed to be true or the test execution is rejected as invalid.

The consequent “C” represents the set of universally quantified statements of the theory that describe the predicted outcome of every execution of a test design. Its logical quantification is also changed to particular quantification to describe the predicted outcome in an individual test execution. In a mathematically expressed theory, “C” may simply be a dependent variable in the equation of the theory. When no value is assigned, it is universally quantified. When the calculated prediction value of the variable is assigned in the individual empirical test execution, it is particularly quantified.

Another particularly quantified statement, “O”, describes the observed test outcome of an individual test execution. The report of the test outcome, “O”, has the same vocabulary that is used in the prediction statement “C”. But the semantics of the terms in “O” is determined exclusively by the universally quantified test-design statements rather than by the statements of the theory, and thus its semantics is independent of the theory’s claims. In an individual predictive test execution “O” represents observations made and data collected after the prediction is made, and it too has particular logical quantification to describe the observed outcome resulting from an individual execution of the test.

If “A” is false in an individual test execution, then regardless of the truth of “C” the test execution is simply invalid due to a failure to comply with its test design, and the status of the theory remains unknown. Contrary to the logical positivists the truth table for the truth-functional Russellian logic is therefore not applicable to testing in empirical science, because a false antecedent, “A”, does not make the hypothetical-conditional statement true. A false antecedent “A” is irrelevant to the truth status of the theory.

The empirical test is conclusive only if it is executed in accordance with its test design.

If “A” is true and the consequent “C” is false, as when the theory conclusively makes an erroneous prediction, then the theory is falsified. Falsification occurs when the statements “C” and “O” are not accepted as saying the same thing within the range of vagueness or measurement-error manifestations of empirical underdetermination. This logic of the test is the modus tollens argument, according to which the conditional-hypothetical statement expressing the theory is falsified, when one denies the consequent clause of the hypothetical conditional. This is the falsificationist philosophy of scientific criticism advanced by C.S. Peirce, the founder of pragmatism, and also advocated by Karl Popper.

If “A” and “C” are both true, the hypothetical-conditional statement expressing the tested theory asserts a causal dependency between the phenomena described by the antecedent and consequent clauses. The hypothetical-conditional statement does not assert merely a Humean constant conjunction. Causality is an ontological category describing a real dependency, and the causal claim is asserted on the basis of ontological relativity due to the empirical adequacy demonstrated by the nonfalsifying test outcome. This is also true when the conditional expresses a numerical correlation. But the empirical adequacy and therefore the causality claim are never absolute or final. Because the nontruth-functional hypothetical-conditional statement is empirical, empirical adequacy and the causality claim are always subject to future testing, to future falsification, and to future revision.

On the pragmatist philosophy a theory that has been tested is no longer theory, once the outcome is known and the test execution is accepted as correct. If it has been falsified, it is merely rejected language. But if it has been tested with a nonfalsifying test outcome, then it is empirically warranted and thus deemed a scientific law. The law is still hypothetical because it is empirical, but it is less hypothetical than it had been as a theory proposed for testing. The law may thereafter be employed in an explanation or in test designs for testing other theories.

For example the engineering documentation for the Tevetron particle accelerator at Fermilab near Chicago, Illinois is based on previously tested science. The science in that engineering is not what is tested when the particle accelerator is operated for experiments, but rather it is presumed true for the experiments performed with the accelerator.
 

Pages << Previous  [1] [2] [3] [4] [5] [6] [7]  Next >>
NOTE: Pages do not corresponds with the actual pages from the book