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  Should Scientific Method be EKS-Rated? 

by Craig Rusbult, Ph.D.

    note: In this page, "EKS" replaces "X" to fool the filtering programs.
    Why should we wonder if scientific methods are EKS-Rated?  The title for this page is borrowed from Stephen Brush (1974) who asks a serious question in a humorous title, "Should the History of Science Be Rated EKS?"  Why is this a relevant question?  Because, as Brush explains in a subtitle, "The way scientists behave (according to historians) might not be a good model for students."

    Should our confidence in science be lessened by the limits of logic and the influence of culture?  This question has sparked heated debates among scholars who hold contrasting views of science.  Since these views seem irreconcilable, it would be futile to aim for a solution that is acceptable to everyone.  Therefore, this page will just discuss issues and express opinions.  I will also make modest recommendations, based on a simple principle — that if a good idea (examining interactions between culture and science) is taken to extremes without sufficient balance from rational critical thinking, there may be undesirable consequences — and an assumption that undesirable consequences should be avoided.
 


 
The SUMMARIES below explain what is in each section,
so you can decide whether to explore it more deeply:

    1. Responsibility in Education
    2. The Limits of Logic
    3. Radical Relativism
    4. Do scientists search for truth?
    5. Science and Unobservables

These section-summaries are followed by a
Table of Contents
that shows subsections
for the five FULL SECTIONS.

and there are two more pages about the ideas in this page:  Tools for Analysis describes concepts and techniques for rationally analyzing the cultural-personal factors that influence science.
 


 
SUMMARIES OF SECTIONS

    Responsibility in Education  (Summary for Section 1)
    We should be deeply concerned about our responsibilities as educators, about the effects that our educational policies will have on students and society.  One way to express this concern is with a thoughtful evaluation of different ways to teach the nature of science.  We should ask, "What description of science is the most accurate, and most beneficial for students?"  But is the answer to both questions the same, in all educational situations?
    Because my model of Integrated Scientific Method (ISM) claims that "cultural factors" affect the process and content of science, ISM can be used to express a wide range of views about "culture in science," including some that may not be accurate or beneficial.  Should this be a cause for concern?
    Is "the way scientists behave (according to historians)" the way scientists really behave?  And if they do, are students better off not knowing?  Are any views of science potentially dangerous?  Should any views be eks-rated (unsuitable for young minds) because they may be harmful for students?  Generally I favor a "free marketplace of ideas" in the classroom, openly discussing a wide range of perspectives.  But if some scholars are advocating views that seem to cross over the line of rationality and good taste, moving into areas that seem foolish or dangerous, should educators avoid these views?  Or is it better to discuss them openly, exposing them to the bright light of critical thinking?
    These questions are discussed in Section 1.

    The Limits of Logic  (Summary for Section 2)
    Yes, there are limits.  It is impossible, using any type of logic, to prove that any theory is either true or false.  Why?  If observations agree with a theory's predictions, this does not prove the theory is true, because another theory (maybe even one that has not yet been invented) might also predict the same observations, and might be a better explanation.  But if there is disagreement between observations and theory-based predictions, doesn't this prove a theory is false?  No, because the lack of agreement could be due to any of the many elements (only one of these is the theory being "tested") that are involved in making the observations and predictions, and in comparing them.
    Or the foundation of empirical science can be attacked by claiming that observations are "theory laden" and therefore involve circular logic, with theories being used to generate and interpret the observations that are used to support theories.  This circularity makes the use of observation-based logic unreliable.  And when this shaky observational foundation is extended by inductive generalization, the conclusions become even more uncertain.
    Yes, these skeptical challenges are logically valid.  But a critical thinker should know, not just the limits of logic, but also the sophisticated methods that scientists have developed to cope with these limitations and minimize their practical effects.  By using these methods, scientists can develop a rationally justified confidence in their conclusions, despite the impossibility of proof or disproof.
    We should challenge the rationality of an implication made by skeptics — that if we cannot claim certainty, we can claim nothing.  Modern science has given up the quest for certainty, and has decided to aim for a high degree of plausibility, for a rational way to determine "what is a good way to bet."
    The question, "Can science cope with the limits of logic?", is discussed in Section 2.

    Radical Relativism  (Summary for Section 3)
    An extreme relativist claims that no idea is more worthy of acceptance than any other idea.  Usually, relativism about science is defended by arguing that, when scientific theories are being evaluated, observation-based logic is less important than cultural factors.  But if theories are determined mainly by culture, not logic, in a different culture our scientific theories would be different.  And we have relativism.
    As with many ideas that seem extreme, radical relativism begins on solid ground.  Most scholars agree with its two basic premises: the limits of logic and the influence of culture.  But there is plenty of disagreement about balance, about the relative contributions of logic and culture in science, about how far a good idea can be extended before it becomes a bad idea that is harmful to rationality and society.
    This section ends by asking, "Does scientific knowledge improve over time?"  Although a skeptic may appeal to the impossibility of proof, "the best way to bet" seems obvious.  To illustrate, we'll imagine a million dollar wager involving a "truth competition" between scientific theories from the past, present, and future: from 1503, 2003, and 2103.  Would a relativist really be willing to bet on theories from 500 years ago?
    The "relativism" question, "Is one idea as good as another?", is discussed in Section 3.

    Do scientists search for truth?  (excerpts from Section 4)
    I haven't yet written a summary for this section, but here are some quotations from it:
    One response to the impossibility of proof is an instrumentalist perspective, in which scientific theories are interpreted as making claims for usefulness, but not for probable truth.  instrumentalism and realism differ in their answer to the question, "Does science try to find truth?"  realism says yes, but instrumentalism says no. .....
    • Section 4A begins by describing two essential components of my own view, critical realism:
    First, a realist can place a high value on both plausibility (an estimate of whether a theory is likely to be true) and utility (an estimate of whether a theory seems to be useful). ... Compared with an instrumentalist — who adopts a restrictive view that eliminates one of the two major criteria (plausibility and usefulness) by excluding a consideration of truth-estimating plausibility — a realist has a wider vision that looks for both plausibility and utility.
    Second, a critical realist (CR) distinguishes between goals and claims.  A CR is a realist about goals, and a critic about claims.  A CR combines realist goals (wanting to find the truth) with critical evaluation (willing to be skeptical about claims for the truth status of a particular theory). ... For example, it is difficult to deny that scientists in the early 1950s who studied the structure of DNA were aiming for a theory that would describe the actual structure of DNA.  They wanted to find the truth, so they were realists.  Before 1953, however, their claims were modest, because all of their theories had a low truth-plausibility.  They were evaluating critically, in an effort to achieve their realist goals.  But after April 1953 the claims for truth became bold, and those who were most knowledgeable quickly decided that the double helix structure deserved to have a very high plausibility because it almost certainly was true.
    Do most scientists usually search for truth?  Yes.  Of course, searching for truth is not the only goal.  Scientists are also motivated by the intellectual stimulation and satisfaction of solving problems, and by practical benefits such as obtaining grants, earning salaries, publishing papers, gaining respect from scientific colleagues and nonscientists, and developing science-based technologies that will bring practical benefits like improved health care or new consumer products.  Yes, all of these are motivations, but it's not an either-or choice, and most scientists also want to construct accurate theories;  they want their theories to be true by corresponding to the reality of what is happening in nature.
    But attitudes toward utility and truth differ in science and design.  An engineer whose main goal is to design an improved product will tend to be more satisfied with viewing a theory only in terms of its usefulness in promoting progress toward this goal, without thinking too much about whether the theory is true.  When a theory is viewed as a practical tool whose function is to be useful during the process of design, the question of truth becomes less important than in science where accurate understanding is the main goal. ..... {there is more in 4A}
    • Section 4B describes arguments for and against instrumentalism.  4C asks a silly question — Do Scientists Create Reality? — and gives a rational answer.  { This answer, plus Reality 101 (basic concepts about distinctions between truth and truth-claims), are in another page. }  4D describes Six Types of Status (relative and intrinsic, pursuit and acceptance, truth and utility) plus two interpretations (realist and instrumentalist) and variable-strength claims about truth.
    The question, "Do scientists search for truth?", is discussed in Section 4.

    Science and Unobservables  (Summary for Section 5)
    A positivist (an empiricist *) believes that scientific theories should not postulate the existence of unobservable entities, actions, or interactions.  By contrast, empirically based hypothetico-deductive logic allows "unobservables" in a theory, if this theory makes predictions (or retroductions) about observable outcomes.  {* empiricist is not the same as empirical }
    Positivism is rare among scientists, who bristle at the constraints, who cherish their intellectual freedom and welcome a wide variety of ways to describe and explain.  Many modern theories include unobservable actions and entities — such as thinking (in psychology) or electrons and electrical force (in chemistry) — among their essential components.
    { terminology:  In the 1830s Auguste Comte, motivated by anti-religious ideology, invented positivism.  In the early 1900s a philosophy of logical positivism combined positivism with other ideas.  Currently, "positivism" has many meanings;  I use it to mean a "no unobservables" constraint, but it can also refer to anything connected with logical positivism (logical empiricism), including the "other ideas" and more. }
    The question, "Should scientists think about unobservables?", is discussed in Section 5.
 


 
Table of Contents

1. Responsibility in Education 

2. Logical Skepticism  
   
2A. Potential Problems and Actual Problems
    2B. Limitations of Hypothetico-Deductive Logic
   
2C. Limitations of Observations
    2D. Limitations of Inductive Logic
    2E. A Summary

3. Relativism  
    3A. Radical Relativism
    3B. Strong Criticisms of The Strong Program
    3C. Two Analytical Tools for Critical Thinking
    3D. Is there Scientific Progress?  A Million Dollar Wager

4. Instrumentalism and Realism  
    4A. Critical Realism
    4B. Pros and Cons of Instrumentalism
    4C. Do scientists create reality?
    4D. Six Types of Status

5. Positivism  
 



 
FULL-LENGTH SECTIONS

 
1. Responsibility in Education

    When selecting a description of science to be used for education, we should ask two important questions:  What is the most accurate description of science, and what educational approach is most beneficial for students?

    ONE FRAMEWORK, MANY VIEWS.   These questions — asking whether a model of science is accurate and beneficial — are important if we want to use ISM in education because:  1) ISM claims that cultural influences [thought styles and cultural-personal factors] affect the process and content of science;  2) there is a wide range of views about cultural influence;  3) ISM can be used to express each of these views.
    For example, a teacher using ISM could claim that although some extremists emphasize the rare cases where cultural factors exert significant influence on the evaluation of scientific theories, for most evaluations the effect of cultural factors is minimal.  This teacher could explain how checks-and-balances occur when a scientific community evaluates claims for knowledge, and how this communal process tends to counteract individual biases.  Or a community could be the source of pressures that produce bias.  This teacher might think that cultural-personal bias is common, but is not a part of authentic science, so it should be avoided.  This could be the entry point for a discussion about sources of bias, and for warnings about the dangers — because bias is detrimental to objective critical thinking, yet is difficult to avoid, tough to detect, and easy to rationalize — along with practical strategies for detecting bias and minimizing its effects.
    Another teacher might criticize "scientific objectivity" because it indicates a lack of cultural conscience.  This could lead to an activist stance with appeals for patriotism or populism, by exhorting students to use science for the benefit of a nation or "the people."
    Or a teacher may prefer the extreme relativism of radical sociologists who propose that a central characteristic of science is the cultural activity of "creating objects and facts" in the laboratory.  This activity produces a relationship in which observations — the supposedly firm foundation for empirical evaluation — are caused by culture, not by nature.  And there is a change in the balance of criteria used for theory evaluation, with a dramatic shift toward cultural-personal factors and away from empirical factors.
    Comparing this radical view of science with a more conventional view, such as my own, we see a sharp contrast.  But both views can be expressed using the framework of ISM.  These "alternative elaborations of ISM" would use the same basic elements — thought styles and cultural-personal factors — but they would propose different characteristics, relationships, and balances, and would therefore propose a different view of science.  { The GOALS-page looks at alternative elaborations, and illustrates by showing how ISM could be used to describe an orthodox view of science (with external consistency and empirically constrained retroduction) or the anarchist ideas of Feyerabend (with external inconsistency and unconstrained counterinduction). }

    THE RESPONSIBILITY OF ISM.   The existence of alternative elaborations is intentional;  ISM is designed to be flexible, so that by varying the characteristics, relationships, and balances of its components, it can be used to describe a wide range of views about science and scientists.  In my opinion, this flexibility is a strength, but it is also a cause for concern.  If wild ideas are expressed using ISM, should I feel responsible, despite my disclaimer that "the opinions expressed using ISM are those of the expresser, and not necessarily those of ISM"?  Maybe.  But in a classrooms the teacher (not ISM or any other instructional tool) makes final decisions about the views that are expressed.  ISM can allow and encourage an accurate description, but cannot guarantee it.
    Is ISM intended to change behavior?  Philosophers of science make a distinction between a descriptive model (that tries to describe science as it actually is done) and a normative model (that tries to describe science as it should be done).  Is ISM descriptive or normative?  With respect to scientists, ISM is descriptive, with no intention of telling scientists how to do science.  But for students, even though the primary function of ISM is descriptive — to allow a complete, accurate description of science as it really is — when any model of science is used in the classroom there will be a normative influence on students.  In fact, promoting a change in student thinking and behavior is the purpose of education, and is the main reason to include a model of science (like ISM) in education.
    Two areas of ISM, cultural-personal factors and thought styles, are especially susceptible to being misunderstood and abused.  Both of these elements are a part of science, so I defend their inclusion in ISM, and a strong case can be made for including them in education.  As usual, however, if this good idea is taken to extremes, with exaggerated interpretations, the result will be a distorted picture of science that is not an accurate description, and is not beneficial for students.

    WHAT IS BENEFICIAL?   It is difficult to answer the "accurate and beneficial" questions with confidence, due to legitimate questions about what constitutes an accurate view of science, and about the effects of what we do in the classroom.  For example, will the enthusiasm of future scientists be dimmed if their role models are tarnished by portrayals of scientists as politically motivated, status-seeking mercenaries?  Or will some students want to become scientists because they see the socially interactive aspects of science, and they realize that scientists are real people, like themselves?  Similar questions can be asked about extreme skepticism.  Will students stop doing experiments if they are told that observations are inevitably biased and unreliable?  And will students stop trying to learn the theories in textbooks if they are told that the justification for these theories is weak or (with anti-realist interpretations) that science does not claim to describe the truth, and does not even try to search for truth?  Or will skepticism merely encourage healthy critical thinking?  And is there a danger when science education becomes politicized so that it argues for certain metaphysical or ideological views?  Or might certain types of politicization be beneficial for students?
    By combining an earlier question (Should the History of Science Be Rated EKS?) with the goals of wanting education to be accurate and beneficial, we can ask whether "the way scientists behave (according to historians)" is the way scientists really behave;  and if they do, are students better off not knowing?  Pedagogical considerations of "what is beneficial" should be heavily influenced by, but not totally determined by, what is regarded as most accurate.  The possible effects on students and society should also be considered.  If something is true, it may seem foolish to ask "Are students better off not knowing?", but this question is worth asking for young students who are not well equipped to cope with complex new ideas or to defend their own ideas.  An essential ingredient in the art of teaching is to judge the intellectual sophistication of students, and then use this awareness to make adjustments so the demands for thinking and learning will be at an appropriate level.
    But should any perspectives really be eks-rated, in the sense that students should not be exposed to them?  In general I favor a "free marketplace of ideas" approach, with an open-minded tolerance for a variety of viewpoints.  In my opinion, a wide range of views about science can be discussed in the classroom, with effects on students that are mostly beneficial, especially if the discussion is done wisely by adjusting the demands for critical thinking to an appropriate level, as described above.  But a responsible educator should avoid the advocacy of views that "cross over the line" of good pedagogical taste, moving into areas that are foolish and even dangerous.  In my opinion, some scholars in the "study of science" community have crossed over this line.  Way over.  Especially with views such as radical relativism and "creating reality."  I oppose these views mainly because I think they are not accurate.  But this inaccuracy can also produce effects that are not beneficial.

    A SUMMARY.   In an effort to act wisely, motivated by an awareness of our responsibilities as educators (or as parents or citizens), we should be deeply concerned with the effects that our educational policies will have on students and society.  This section began by asking, "What is the most accurate description of science, and what educational approach is most beneficial for students?"  These questions are worth asking, even though (or because) there are no simple answers.  Instead of seeking a solution that will satisfy everyone, which is impossible, the goal of our question-asking should be to stimulate a thoughtful evaluation of the merits of different approaches to teaching the nature of science.  And while we're doing this, we can think about how our evaluations are being influenced by our individual and collective perspectives on the complex relationships between models of science, quality of education, and quality of life.
 

Summaries
Table of Contents

 


 

2. The Limits of Logic

    The limits of logic are summarized in a principle of underdetermination which states that it is impossible, using any type of logic, to prove that a theory is either true or false. 

    In a reversal of the usual pattern, I'll begin with my conclusions (in Section 2A) before discussing the skeptical challenges to hypothetico-deduction, observation, and induction.

2A. Potential Problems and Actual Problems 
    Logical skepticism is based on sound principles.  A critical thinker should be aware of the limitations of observations, and of logic that is hypothetico-deductive, retroductive, or inductive.  But although some skepticism is good, too much of this good thing — without sufficient balance by thinking critically about the claims of skeptics — can be detrimental to science and rationality.
    In extreme logical skepticism there is a tendency to ignore the distinction between potential problems and actual problems, and to therefore propose "cures for which there is no adequate disease. (Fodor, 1986)"  If extreme skeptics assume that modern science aims for certainty, they are wrong.  In response to claims that nothing can be proved, most scientists would simply say "So what?", because instead of asking "What can be proved using formal logic?" it is more practical for scientists to ask "What is a good way to bet?"   Scientists have developed methods for coping with the concerns of skeptics, so that in most situations the skeptics' potential problems do not seem to be significant actual problems for science.
 

note: For access to references (such as "Fodor, 1986"), check the end of this page.
 

2B. Limitations of Hypothetico-Deductive Logic 
    If observations agree with a theory's predictions, skeptics correctly point out that this does not prove the theory is true, because another theory — including one that has not yet been invented, and maybe never will be invented — might also predict the same observations, and might be a better explanation.  And when a theory is invented using retroductive logic (which is a variation of H-D logic, subject to the same limitations) an additional reason for caution is that this theory is being constructed so it will fit known data, and empirical agreement can be obtained by ad hoc patchwork.
    The "Overview of Scientific Method" describes one method for coping with this logical difficulty:  "A theory can be false even if its predictions agree with observations, so it is necessary to supplement this 'agreement logic' with another criterion, the degree of predictive contrast, by asking "How much contrast exists between the predictions of this theory and the predictions of plausible alternative theories?" in an effort to consider the possibility that two or more theories could make the same correct predictions for this system."  { a detailed explanation of predictive contrast — and the "So What?" question — is on the "Details of Scientific Method" page }

    Compared with the impossible task of proving a theory is true, it is generally considered easier to gather evidence showing that a theory is inadequate.  Popper (1963) emphasizes the asymmetry between verification and falsification:  if a theory predicts "if T then O, and T occurs" and O also occurs, this does not prove T is true;  but if O does not occur, this proves T is false.
    Despite this valid logic, it still is impossible to logically prove a theory is false, because if there is anomaly for a theory (due to a low degree of agreement between predictions and observations) the disagreement could be due to any of the many elements that contribute to the predictions, the observations, and their comparison.  Erroneous predictions could be caused by an inadequate theory or supplementary theory, or by a characterization of the experimental system that is inaccurate or incomplete, or by mis-applying theories to construct a model, or using faulty deductive logic to make a prediction.  But perhaps it is the observations that are not reliable, due to poor experimental design or sloppy technique; or maybe there was defective equipment, such as an observation detector that did not function as expected.  Or the logic used in comparing the predictions and observations may be deficient, and this has produced an estimated degree of agreement that is inappropriately low.
    There are many possible causes for anomaly, and each can be illustrated with examples from the history of science.  A rigorous logical analysis (Duhem, 1906; Quine, 1953) leads to the skeptical conclusion that anomaly cannot ever be localized to any of these possibilities.  But according to Shapere (1982, p. 516), "What this shows is that formal logic does not exhaust what counts as reasoning in science."  Scientists are quite willing to use "reasoning that goes beyond formal logic" to cope with a complex situation and to make educated estimates — based on their confidence in each factor that affects the predictions, observations, and comparison — about where the anomaly is likely to be located.

    Another reason for the impossibility of proof or disproof comes from the statistical nature of some predictions and observations.  For example, Grinnell (1992) discusses the differences in logic between three theoretical claims:  "All X are Y" can be falsified but not verified;  "Some X are Y" can be verified but not falsified;  and "90% of X are Y" cannot be verified or falsified.
    Most scientists will agree with these conclusions about what can and cannot be proved.  But skeptics will challenge the first two claims, which assert that a theory "can be verified" or "can be falsified."  And scientists will challenge the pessimistic conclusion that the third claim "cannot be verified or falsified" because a sophisticated statistical analysis of data can lead to a rationally justified confidence about the truth or falsity of a statistical claim such as "90% of X are Y."  But skeptics will question whether this confidence is justified. 

    According to formal logic, a theory can never be proved true.  But sometimes a theory correctly predicts old and new data for a wide variety of experimental systems, even though the combined empirical constraints (for all experiments) are so demanding that it seems unlikely any alternative theory could also satisfy them.  This is why, for example, few scientists doubt the double-helix structure of DNA, despite valid logical arguments that this theory is underdetermined by the data. 
    Even though it is logically impossible to prove that any theory is either true or false, scientists can have a rationally justified confidence that a particular theory is true, or at least approximately true.  Or they may be confident that it is false.
    Most scientists will say that an extreme skeptic is wrong in implying that if science cannot claim certainty, it can claim nothing.  Modern science has given up the quest for epistemological certainty, and is willing to settle for a high degree of plausibility.  Scientists rarely worry about skeptical challenges such as "Can you be certain the sun will rise tomorrow?" (argued by Hume), or "How do you know it isn't all a dream?" (asked by Descartes), or "Can you prove that scientific theories of today are closer to the truth than theories of 500 years ago?" (a challenge by extreme relativists).  When it comes to theory evaluation, instead of asking "What can be proved using formal logic?", it is more practical for scientists to ask "What is a good way to bet?"

    Consistent with the lack of certainty in science, in ISM the concept of status uses a continuum to estimate the degree of confidence in a theory.  And the definition (from Giere, 1991) of hypothesis — as a claim that a system and a theory-based model are similar in specified respects and to a specified (or implied) degree of accuracy — allows flexibility in defining what is (and is not) being claimed for a theory.  In addition to status and variable-strength hypotheses, other types of status (intrinsic and relative, for pursuit and acceptance, for truth and utility) can be used to modify and thus to more accurately describe the results of evaluation.

 

2C. Limitations of Observations 
    For skeptics, another option is to attack the foundation of empirical science by claiming that observations are biased and unreliable.  Some challenges are described below, along with the methods {in brackets} that scientists have developed in order to cope with each potential difficulty.

    Why is data collection biased?
    During experimental design, scientists decide what to study and how to study it, and this decision determines the data that will be collected.   { The effects of experimental design can be analyzed, so these effects can be considered during data interpretation and during the design of future experiments.  More important is the fact that even though design determines the types of data, nature determines the data. }
    Data will be biased if it is collected by a human who has expectations for what is worth seeing or what will occur, or who hopes that certain results will occur.   { This is a valid concern that varies with the situation.  In a medical experiment there will be little concern if an observation arises from reading a digital thermometer.  But if subjective assessments of patients' symptoms are required, scientists often use a "double blind" experimental design that minimizes errors due to observational bias at a conscious or unconscious level. }

    Why are "theory-laden observations" a cause for concern?
    Circular logic occurs because theories are used to generate and interpret observations that, in turn, are used to support theories.  { If the theory being evaluated is closely related to an observation-theory used in an experiment, with overlapping domains and many shared assumptions and theory components, concerns about circularity are justified.  But if a theory and observation-theory are relatively independent, there will be minimal circularity.  Shapere (1982, pp. 514-516) discusses logically sophisticated methods for analyzing observation situations and observation theories, and how scientists use these methods to check for circularity and reliability. }
    Observations depend on theories, and theories are uncertain, so this lack of reliability transfers to our observations.  { As discussed above, scientists can have a rationally justified confidence about the plausibility of theories, including observation-theories concerning the source, the transmission process, and the receptor for what is being observed (Shapere, 1982). } { details }
    Theory-based interpretations always occur during observations.  { Yes, but the influence of interpretation is limited.  As noted by Strike (1987), although in the early 1600s an Aristotelian scientist and Galileo would "see" a pendulum differently, neither would see a giraffe. }

 

2D. Limitations of Inductive Logic 
Skeptics can claim that:
    Observations are unreliable.  When this shaky foundation is extended by inductive generalization that is based on the unreliable observations, the conclusions become even more unreliable and uncertain.  { The first and second parts of this argument are discussed above and below, respectively. }
    But even when observations seem reliable, induction is not logically justified.  For example, David Hume asked "Can you be certain the sun will rise tomorrow, based on inductive generalization from its behavior in the past?"  { According to formal logic the answer is NO.  But science assumes the answer is YES unless there is a reason to believe the behavior will change.  Induction cannot be proved, but scientists consider it a good way to bet.  /   Instead of adopting a total skepticism, scientists use statistical logic and statistical conclusions.   They also try to understand the distinction between different types of inductions, involving different types of systems and properties.  For example, most scientists would be more confident about a generalization that "all pure NaCl is white," compared with the analogous claim that "all swans are white."  Philosophers explain the relative difference in confidence in terms of differences in "lawlike" and "accidental" character, and there are logical reasons to believe that the whiteness of NaCl has more lawlike character than the whiteness of swans. }

 

2E. A Summary 
    It is logically impossible to prove a theory is either true or false.  Why?  Hypothetico-deduction has logical limitations (because even when a prediction is "if A then B" and we observe B, this does not prove A) and there can be suspicions about ad hoc adjustments when (in retroductive inference) a theory is proposed to fit known data.  Other difficulties include biased data collection, circularity between theories and observation-theories, and the logical limitations of inductive generalization.
    In an effort to cope with their own concerns about these logical limitations, scientists have developed methods — including estimates for predictive contrast, and sophisticated techniques for logical analysis — that encourage them to claim a "rationally justified confidence" for their scientific conclusions, despite the impossibility of proof or disproof.

 
Summaries
Table of Contents

 


 

3. Radical Relativism

Taken to an extreme, relativism claims that no idea is more well founded, and deserving of acceptance, than any other idea.
 

3A. Logic and Culture 
    Relativism about scientific theories is usually defended by combining two premises, by claiming that during theory evaluation:  1) due to the limits of logic (discussed above), observation-based logic exerts only a weak influence, but  2) a strong influence is exerted by cultural-personal factors.  If logical input is weak and cultural influence is strong, with ideas determined mainly by culture, then in a different culture the results of theory evaluations would be different.   { What are cultural-personal factors? }

    While there is a correlation between a heavy emphasis on cultural factors (in science process) and relativism (in science content), there is no necessary link.  For example, Hull (1988) thinks that reliable content can emerge from a chaotic process.  So does Bauer (1992), who claims that during a communal "filtering" process the non-objective behavior of individuals (or small groups) tends to cancel, thus producing a result that is more objective than the objectivity of individual scientists.  /   In addition to a heavy emphasis on culture, relativism seems to also require an extreme form of logical skepticism that challenges the credibility (or even the possibility) of culturally-independent empirical "reality checks" that might compete with cultural influence.
    Or, instead of asking why scholars reach relativism as a conclusion, perhaps it makes more sense to assume that — due to cultural factors operating in society and in scholarly communities — a preference for relativism comes first, followed by the arguments (involving logic and culture) that are enlisted as support.

    In recent decades, radical relativism has become surprisingly popular among scholars.  A catalyst in the rise of relativism was The Structure of Scientific Revolutions (Kuhn, 1962), which emphasized the role played by non-logical factors in the revolutionary overthrow of one paradigmatic "way of thinking" by another.  This book helped inspire a wave of anti-rationalist intellectual activity that pushed the boundaries of relativism far beyond the original claims of Kuhn.
    One group pushing the boundaries, the "strong program" in the sociology of scientific knowledge, has focused on the ways in which cultural-personal factors affect the content of science.  This is more controversial than claims about the process of science, which is generally agreed to be influenced by social factors.  Scholars in the strong program usually adopt a radical relativism, claiming that the content of scientific theories is influenced more by culture than by nature. (or at least they claim that we should assume culture is stronger than nature, when we are studying the process and content of science)

 

3B. Strong Criticisms of The Strong Program 
    Many critics have described the logical deficiencies of extreme perspectives such as the Strong Program that is outlined in Knowledge and Social Imagery (Bloor, 1976, 1991) and is manifested in Laboratory Life (Latour and Woolgar, 1986):
The claims of contemporary SSK [sociology of scientific knowledge]... for the external causation of scientific beliefs are baseless. ...  When distilled to its essence, the entire "argument" [of Bloor]... is just this spurious inference from underdetermination to social construction. ...   [Latour and Woolgar (1986, p. 273) claim that their] own work, then, just like all of science, has no determinate meaning since, as they explain, "It is the reader who writes the text."  This move, a characteristic feature of Deconstructionist writings, has the effect of showing any critic to have ipso facto failed to understand the subtlety and sophistication of the work.  In particular, the use of logic and the traditional categories of thought is sufficient evidence of a critic's misunderstanding.  (Slezak, 1994, pp. 265, 283, 332)
 
According to Slezak, radical relativism produces destructive effects on society that extend far beyond the realms of scholarly discourse where these ideas originate:
The enterprise of SSK and the wider post-modernist fashion for textualist, historicist relativism can be seen to corrupt the standards of critical thought and honest inquiry. ...  This responsibility of intellectuals to speak the truth and to expose lies is also the responsibility of teachers to instill.  Above all, it is the responsibility of science teaching to convey what Bronowski called "the habit of truth" which is central to the scientific enterprise.  (Slezak, 1994, pp. 289-290)

    One of the most harmful features of radical sociology is that, in important ways, it can undermine the conventional view that "a central aim of education... is the fostering of rationality, or its educational cognate, critical thinking. (Siegel, 1989, p. 21)"
    Slezak and Siegel are not alone in their distaste for extreme relativism.  Their views are shared by many scholars, including myself and Laudan (1990, p. x) who declares that "The displacement of the idea that facts and evidence matter by the idea that everything boils down to subjective interests and perspectives is... the most prominent and pernicious manifestation of anti-intellectualism in our times."  Therefore, it is disturbing to see large segments of the intellectual community either approving radical relativism, or not being active in arguing against it.

    Briefly stated, my opinion, based on the principle that without balance "too much of a good thing" can be harmful, is that extreme relativism is the result of taking useful ideas — such as critical thinking, logical skepticism, and an awareness of cultural-personal factors — and stretching them to the point where they not only lose intellectual credibility, but they become dangerous for science and society.

 

3C. Two Analytical Tools for Critical Thinking 
    When evaluating extremist interpretations of science, it helps to have tools that encourage flexible critical thinking and precise, accurate conclusions.  I have developed two useful tools for analysis: idealizations and range diagrams.   These tools can facilitate a critical examination of the ways that science is influenced by cultural-personal factors, and will help avoid dichotomous generalizations such as "no cultural influence" or "all cultural influence."
    The use of idealizations to study science is based on the principle that an oversimplified model can be useful for estimating the effects of a component that has been intentionally omitted from the model.  In this case, cultural-personal influence is studied by trying to imagine what science (especially as it is exemplified in a specific historical episode) would be like without this influence, and comparing this idealization with the actual science.
    The second type of analytical tool, range diagrams, can be used to help determine how accurately a sample represents a larger population, and in deciding what conclusions can be drawn about a population based on a small sample of case studies.  For example, when studying the mutual influence between societal politics and science, different conclusions will result from studying a sociobiologist (this field can be very politicized) and a benzene chemist (very little societal politics is happening here).  Although each scientist is part of the total science experience, drawing a general conclusion based on either sample by itself would be misleading.

    These tools are useful for recognizing cultural influence without overemphasizing it.  And they help clarify my own views, to minimize misunderstandings.  When I criticize extreme relativism, I am not claiming that cultural influence is negligible.  My model of Integrated Scientific Method contains cultural-personal factors (such as psychological motives and practical concerns, metaphysical worldviews, ideological principles, and opinions of authorities, operating in complex social and institutional contexts) because these factors play a role in the process of science and (usually to a lesser extent but not always) in the content of science.
    The tool of idealization is useful for recognizing bias and coping with its effects, as recommended by the first teacher of Section 1, who is expressing my basic views.  And range diagrams are useful for avoiding generalizations that oversimplify and distort, for recognizing that cultural-personal factors play different roles in different areas of science and in different communities within each area, and exert different influences on the process of science and on the content of science.

 

3D. Is there Scientific Progress? A Million Dollar Wager 
    Although to most of us the answer is obvious, skeptics can challenge a claim that scientific knowledge improves over time.  The progress in scientific utility is clear.  But progress in truth is impossible to verify, since none of us can be sure we know the truth, so a skeptic asks "Can you prove it?"  My brief answer is "no, but it's a good way to bet."

    For example, consider a million dollar wager.  Imagine that 1000 scientific theories from the year 2003, covering a wide range of fields, are compared with 1000 corresponding theories from 600 years earlier, in 1403.  You can choose one set of theories, either 1403 or 2003, and someone who knows the truth about nature — such as an omniscient being (God?) or an alien from a scientifically advanced civilization — decides which theory (in each of the 1000 areas) is closer to this truth.  If your theory is more true, you win $1000, but if the other theory is more true you lose $1000.  Should you care which set of theories you get?  According to those who claim that science does not improve with age, it should not matter.  If there is no scientific progress, the 1403-science and 2003-science have an equal chance of being closer to the truth.  In my opinion, anyone who is not a fool (or who wants to give away a million dollars) should have a rationally justified confidence, although no proof, that the science of today is a better way to bet.
    For a rough estimate of how superior you think the theories of 2003 are, consider a wager with two options: you can pay $600,000 and choose the theories of today, or decide not to play.  If you play, you break even with a 20-80 split between the theories of 1403 and 2003.  I would eagerly pay the entry fee, with confident assurance that I would win roughly $400,000.  Would you take the bet if the fee was changed to $800,000, so you need a 10-90 split to break even?  What do you think the majority of scientists would do?  I think most would take the bet, even if they had to pay $900,000 for the chance to win $100,000.  After all, 1-to-9 odds aren't too shabby when betting on 600 years of scientific progress.
    Please notice that I'm not saying all theories of 2003 are perfect, just that in general they are better than the theories of 1403.  If our theories continue to apparently improve (as they have in the past), then in a million dollar wager comparing theories of 2003 and 2103, I would bet against our current theories.

 
Summaries
Table of Contents

 


 

4. Do scientists search for truth? (Instrumentalism and Realism)

    One response to the impossibility of proof is an instrumentalist perspective, in which scientific theories are interpreted as making claims for usefulness, but not for probable truth.  Instrumentalism and realism differ in their answer to the question, "Does science try to find truth?"  Realism says yes, but instrumentalism says no.

    Section 4A explains my view, Critical Realism.  { realist goals with critical evaluation }
    4B describes the Pros and Cons of Instrumentalism.  { some arguments for and against }
    4C asks a silly question — Do Scientists Create Reality? — and gives a rational answer.
    4D describes Six Types of Status.  { concepts for precise thinking and communicating }
    You can read these sections in any order you want.

 
4A. Critical Realism
 
    It is difficult to define either realism or instrumentalism with precision, because in real life there is a range of realist views, and a range of instrumentalist views.  In our efforts to to decrease inaccurate stereotyping, to more accurately understand and portray the characteristics of individual views, a useful thinking tool is offered by Leplin (1984).  He describes ten claims that a realist may or may not believe;  by affirming or denying various claims, a variety of realist positions is possible, ranging from modest to strong.  This analysis shows that more is involved than a simple "modest to strong" continuum, since the short-list of claims made by one modest realist may differ from the claims of another modest realist.  Instrumentalist positions are similarly variable.  Therefore, when discussing this topic it is important to avoid either-or dichotomies that lead to distorted oversimplifications.  This section describes one type of realism — critical realism — that offers many practical benefits.

    When thinking about critical realism, two concepts are crucial.
    First, a realist can place a high value on both plausibility (an estimate of whether a theory is likely to be true) and utility (an estimate of whether a theory seems to be useful).  This is summarized in my definition of theory status as an estimate of "a theory's plausibility and/or utility."  For a realist, the relative importance of plausibility and utility can vary from one theory to another, or even from one application of a theory to another.  Compared with an instrumentalist — who adopts a restrictive view that eliminates one of the two major criteria (truth and usefulness) by excluding a consideration of truth-estimating plausibility — a realist has a wider vision that looks for both plausibility and utility.
    Second, a critical realist (CR) distinguishes between goals and claims.  A CR is a realist about goals, and a critic about claims.  A CR combines realist goals (wanting to find the truth) with critical evaluation (willing to be skeptical about claims for the truth status of a particular theory).  As explained in Section 4D, realism (for goals) is compatible with criticism (of plausibility).  For example, it is difficult to deny that scientists in the early 1950s who studied the structure of DNA were aiming for a theory that would describe the actual structure of DNA.  They wanted to find the truth, so they were realists.  Before 1953, however, their claims were modest, because all of their theories had a low truth-plausibility.  They were evaluating critically, in an effort to achieve their realist goals.  But after April 1953 the claims for truth became bold, and those who were most knowledgeable quickly decided that the double helix structure deserved to have a very high plausibility because it almost certainly was true.

 

4B. Pros and Cons of Instrumentalism 
    What is the status of the main alternative to realism?  Laudan (1984) clearly expresses the two most common arguments in favor of instrumentalism:
    One argument is that the components of many abandoned theories were once considered real, so why should we be confident that the components of current theories will not meet this same fate?  But this ignores the analogous counter-argument:  History also provides many examples of postulated components (for entities, actions, or interactions) that are still considered valid.  And sometimes postulated components that initially could not be observed became observable when improved observation technologies and techniques were developed.  Laudan's argument depends on inductive "boy who cried wolf" logic that is not deductively valid and also, as just described, is opposed by many counter-examples.  And it seems to imply that, in a contest of "1403 vs 2003", the fact that current theories consistently win should be counted as evidence against the possibility that these theories might be true, or at least approximately true.
    In my opinion, the strongest argument for the reality of many components of modern theories is that it seems extremely unlikely that these theories could make accurate predictions if none of their components (or very few of them) corresponds to what is actually happening in nature.  In other words, a claim that "this theory is true, or is at least approximately true" seems to be a plausible explanation for why the theory can make accurate predictions.  This is not a proof, of course, but it does seem like a rational way to bet.
    Laudan's second argument is that a goal is "utopian" if there can never be a way to know whether it has been achieved.  Since the truth of a theory can never be proved, we can never know if we have achieved a realist goal, so this utopian goal should not be held by rational scientists.  Compared with his first argument, I find this one more impressive.  But I remain unconvinced, for reasons similar to the "best way to bet" arguments against logical skepticism.  Even though there is no way to prove a theory is true or false, scientists can have a rationally justified confidence about it, and this is all that most modern scientists expect.  More important, we should remember that the defining characteristic of realism is a goal (our search for truth), not a claim (for certainty about truth).

    To say that scientists do always think instrumentally is inaccurate*, and to demand that scientists should always think instrumentally (by never thinking of a theory in terms of its possible truth) is too restrictive.  { * In my experience, most scientists have difficulty even understanding the concept that scientists don't try to search for truth, and they certainly don't agree with it. }  Compared with instrumentalism, the eclectic "best of both" framework offered by critical realism is a much better way to describe the actual practice of science, because this framework flexibly accommodates the fact that both types of thinking (in terms of utility and truth) are used in science, with the relative proportions depending on the scientist and the situation.
    Attitudes toward utility and truth also differ in science and design.  An engineer whose main goal is to design an improved product will tend to be more satisfied with viewing a theory only in terms of its usefulness in promoting progress toward this goal, without thinking too much about whether the theory is true.  When a theory is viewed as a practical tool whose function is to be useful during the process of design, the question of truth becomes less important than in science where accurate understanding is the main goal.

    Do most scientists usually search for truth?  Yes.  Of course, searching for truth is not the only goal.  Scientists are also motivated by the intellectual stimulation and satisfaction of solving problems, and by practical benefits such as obtaining grants, earning salaries, publishing papers, gaining respect from scientific colleagues and nonscientists, and developing science-based technologies that will bring practical benefits like improved health care or new consumer products.  Yes, all of these are motivations, but it's not an either-or choice, and most scientists also want to construct accurate theories, theories that match the reality of what is happening in nature.

    Webster's New Collegiate Dictionary defines instrumentalism as "a doctrine that ideas are instruments of action and that their usefulness determines their truth."  Does this doctrine make sense?  An idea may be useful because it is true, and its usefulness may be an indication of its truth.  But an idea cannot be true — in the sense that it corresponds to reality (*) — because it is useful.   { * And if we adopt any other meaning of "true", this word loses its usefulness.  With any other meaning, the essential concept of "truth" is removed from our vocabulary, and the loss of an important concept should be avoided, even by those who disagree with the concept. }
    What is the relation between instrumentalism and postmodernism?  There is a partial correlation.  Arguments against truth as a goal (and even against truth as a concept!) are especially popular among scholars who get excited about postmodern theories based on radical relativism.  But anti-realist perspectives are also held by scholars who don't have postmodernist views.  A postmodernist is usually (or always?) an instrumentalist, but an instrumentalist may not be a radical relativist or a postmodernist.
    As explained in Section 4A, there is "a range of instrumentalist views."  I have intellectual respect for instrumentalists who refuse to make the arrogant claim that "usefulness determines...truth"), who are humble in their claims about the power of theories to determine truth (a theory can influence cultural worldviews about what they think the truth is, but this is not the same as determining what the truth actually is, as explained in Section 4C), who say "an instrumentalist is not claiming (or denying) that if a theory is useful then this makes it true (by making it correspond with reality), since the claims being made are actually more modest than those of a realist, with an instrumentalist making claims only about a theory's usefulness."
    By contrast, the following section shows the foolish self-delusion that occurs when people become arrogant about the power of their own ideas.

 

4C. Do Scientists Create Reality?
Do scientists study nature, or create nature?  Somewhat amazingly,
Woolgar (1989) argues that scientists construct objects through their representations of them.  Objects, according to Woolgar, whether they are countries or electrons, are socially constructed entities, and do not exist aside from this social construction.  Science is therefore not the process of finding things that already exist, but the process of creating things that were not there to begin with.  (Finkel, 1993, p. 32)
In the words of Latour & Woolgar (1979, p. 64), "The bioassay is not merely a means of obtaining some independently given entity; the bioassay constitutes the construction of the substance."   Matthews (1994, p. 152) comments on this type of wild claim — that "objects do not lie around ready made in the world but are mental constructs (Wheatley, 1991, p. 10)" — by explaining a crucial distinction: "Where he [Wheatley] goes wrong is in failing to distinguish the theoretical objects of science, which do not lie around, from the real objects of science, which do lie around and fall on people's heads."
 
A description of the way scientists typically think about the observation of real objects (no, it is not necessary to "create the reality" of the objects) is provided by a cell biologist:
First, I assume that cells are real objects.  Second, I assume that other people can see and think about things the way that I do. ...  Others' basic experience of reality is similar to mine.  If they were standing where I am standing, they would see something very similar to what I see. ...  Scientists act as if...the observations made by one scientist could have been made by anyone and everyone.  (Grinnell, 1992, p. 20; emphasis in original)
 
Another excellent description of "truth" and "reality" is provided by a philosopher:
Whether a statement is true is an entirely different question from whether you or anybody believes it. ...  There can be truths that no one believes.  Symmetrically, there can be beliefs that are not true. ...  The expression "It's true for me" can be dangerously misleading.  Sometimes saying this... means that you believe it.  If that's what you want to say, just use the word "belief" and leave truth out of it.  However, there is a more radical idea that might be involved here.  Someone might use the expression "true for me" to express the idea that each of us makes our own reality and that our beliefs constitute that reality.  I will assume that this is a mistake.  My concept of truth assumes a fundamental division between the way things really are and the way they seem to be to this or that individual mind.  (Sober, 1991, pp. 15-16)
 
    There are two types of reality, internal and external: the reality of what an individual (or community) believes, and the reality of what is.  What label should we attach to the first type of reality, the reality of what occurs within one or more minds?  We can call it a belief, theory, hypothesis, opinion, premise, conclusion, worldview, principle, conviction,... but we should not call it truth (as if our theories about something will cause our theory about it to become true) and we should not make the mistake of believing that our internal thoughts will determine external reality.  Our thoughts will influence some things (our own actions) but not other things.  { A good illustration of "external reality" is the question of "solar system reality" that concludes this section. }
    Sober illustrates what he considers to be a valid meaning for "thoughts becoming reality" by describing a situation in which a person's thoughts (he thinks he won't hit a baseball) affect his actions (he swings too high), thus causing a result (he doesn't hit the baseball).  By contrast,
What I do deny is that the mere act of thinking, unconnected with action or some other causal pathway, can make statements true.  I'm rejecting the idea that the world is arranged so that it spontaneously conforms to the ideas we may happen to entertain.  (Sober, 1991, p. 16)

    My comments and the quotations above, from a scientist (Grinnell) and a philosopher (Sober), summarize the most important concepts in "Reality 101" so I'll just close this section with an example from science:  Anyone who really thinks that "beliefs create reality" should be eager to explain how the real motions of all planets in the solar system changed from earth-centered orbits in 1500 (when this was believed by almost everyone) to sun-centered orbits in 1700 (when this was believed by almost all scientists).  Did the change in beliefs (from theories of 1500 to theories of 1700) cause a change in reality (with planets beginning to orbit the sun at some time between 1500 and 1700)?

 

4D. Six Types of Status, plus Interpretations and Claims 
    As a reminder that the outcome of theory evaluation is an educated estimate rather than a claim for certainty, my model of Integrated Scientific Method (ISM) uses a continuum of theory status, ranging from very low to very high, to describe our degree of confidence in a theory.  To allow a more precise description of theory status, eight additional distinctions are useful.

    Each theory has six types of status (in three pairs) and an interpretation, plus a range of claims:
    1a.  Each theory has relative status (compared with alternative theories) and intrinsic status.
    1b.  Each theory has pursuit status and acceptance status.  As suggested by Laudan (1977), even if a theory is not judged to be worthy of acceptance, scientists can rationally view this theory as worthy of pursuit (for continuing development, application, and testing) if it seems to have potential for developing in ways that will improve its plausibility and utility, or is useful (even in its current form) for stimulating new experimental or theoretical research.
    1c.  Each theory has truth status and utility status.  /   In ISM, truth status is an estimate of the similarity between the composition-and-operation of real systems and the composition-and-operation of models (for these real systems) that are constructed by using the theory.  { Here, I am using a correspondence definition of truth, which says "a theory is true if it corresponds to what actually exists."  I think this is the only meaning worthy of being called "truth", and is the only definition we should use. }  Truth status (which I call plausibility) is a human estimate for the probability of truth, rather than a claim for the certainty of our knowledge about truth.  /   A theory's utility status is an estimate of the overall usefulness of this theory, including scientific utility for cognition and research and (if utility is defined more broadly) for cultural-personal usefulness.
    2.  Each theory can be viewed with a realist interpretation (in which scientists think this theory is intended to have two types of function: to be useful and to describe what really occurs in nature) or an instrumentalist interpretation (that this theory is intended only to be useful, and does not claim to describe reality).  This interpretation can vary along a continuum from pure realist to pure instrumentalist.  A "degree of realism" interpretation is independent from estimates of plausibility and utility.  For example, a scientist may think that a particular theory is intended to portray reality (so there is a realist interpretation) but does not do this very well (so it has a low plausibility).  Also, a realist interpretation is compatible with a strong emphasis on utility, since a theory can aim to be both true and useful.  {back to 4B}

    3.  Another "flexibility concept" helps us think more precisely about specific applications of a general theory.  When a theory is used to construct a theory-based model of a particular experimental system, scientists can use variable-strength hypotheses to make different "similarity claims" for this system-and-model.  The plausibility estimate (for truth status) that is an outcome of evaluation can vary with the strength of a hypothetical claim.  A strong claim (for an exact match between all features of a theory-based model and the real system) may have lower truth status than a weaker claim (for a similarity that is approximate rather than exact, or for a similarity between some features but not all).   { more details about the concept of variable-strength hypotheses }
    This definition of hypothesis (from Giere, 1991) refers to claims about the similarity between a model and system, and is thus oriented toward truth status, which is relevant only with a realist interpretation.  But we can also think of variable-strength hypotheses as making different claims about the expected degrees of agreement between predictions and observations.  For example, a medium-strength hypothesis might claim there will be a close match for some predictions, but a less exact match for other predictions.  This emphasis on "predictive utility" would be compatible with either realist or instrumentalist interpretations.  Or there might be differing strength-claims about other aspects of a theory's scientific utility. 

    THE UTILITY OF THESE CONCEPTS.  Some terms in this section (pursuit and acceptance, plausibility and utility, realism and instrumentalism) are commonly used in philosophy, while others (intrinsic status and relative status, truth status and utility status) have been defined by me, and one (hypothesis) is used with a variety of different meanings.  Only a few of these terms (acceptance, plausibility, hypothesis) are common in the language of scientists, but I think all of the concepts are common in the thinking of scientists.
    These concepts are useful because, instead of forcing ideas into the narrow channels of rigid language, they encourage flexible thinking.  They do not limit a thinker to dichotomous alternatives such as acceptance or rejection, verification or falsification.  These binary categories are still available — because if status rises above a certain level we can think in terms of acceptance, and if it falls too low we can choose to reject — but a "yes or no" choice is not forced on us prematurely because our rigid concepts have limited the options we are capable of creatively imagining and thoughtfully considering.
    In a community of critical thinkers, this system of concepts (*) will encourage thinking and communication that is more accurate and precise, whether we are evaluating a theory or describing the scientific methods used in specific situations or in general.  And in a classroom, these concepts will encourage students to think and communicate more carefully, with increased precision.  {* Sometime soon, I'll be organizing these concepts into a logical framework that is coherent yet flexible. }

The basic concepts of reality are examined more closely in Reality 101.

Summaries
Table of Contents

 


 

5. Positivism (science and unobservables)
    One way to avoid some limitations of hypothetico-deductive (HD) logic is to avoid speculating about anything that is not observable.  Positivism is the claim that scientific theories should not postulate the existence of entities, actions or interactions that cannot be directly observed.  By contrast, empirically based hypothetico-deductive logic allows "unobservable" components in a theory, if this theory makes predictions (or retroductions) about observable outcomes.  As explained in my page defending The Reliability of Historical Science against attacks by postmodern skeptics and young-earth creationists,
Can scientists logically infer the existence of things they cannot observe?  Yes, if an unobservable cause produces observable effects.  This cause-and-effect principle is used in operations science.  For example, even though electrons and ideas cannot be observed, modern theories propose electrons (in chemistry) and ideas (in psychology).  Why?  Because our observations are explained in the most satisfactory way by theories proposing the existence of unobservable causes (electrons and ideas) that produce the effects we observe.

    The motivations for positivist constraints can be due to beliefs about utility (what is useful) and/or ontology (what exists).
    utility:  One motivation for positivist philosophy is to build science on the firm foundation of empirical observations, thereby making scientific knowledge more certain.
    ontology:  Or positivists may want to purge science of metaphysical proposals for unobservables.  But most philosophers have concluded that positivism does not necessarily make science more certain;  and instead of making science non-metaphysical, it simply replaces one type of metaphysics with another type.

    In the early 1900s, very few scientists decided to abandon atomic theory (even though this abandonment was being urged by Ernst Mach, based on positivist principles) or to stop thinking in terms of "forces" (which have been considered unobservable by many positivists).  But positivist perspectives did dominate two major fields, psychology and philosophy of science, for several decades in the first half of the twentieth century.  Behaviorist psychology, based on positivist limitations, enjoyed a quarter-century reign of dominance, but since the 1950s it has been surpassed by a less restrictive cognitive psychology (whose focal point is unobservable cognitive activities within the brain) that has provided a liberating perspective for most psychologists.  And the influence of logical positivism, which was the dominant philosophy of science for several decades, has declined dramatically.
    Although positivism was once a popular perspective in philosophy, this view has always been rare among scientists (except temporarily among psychologists) because they welcome a wide variety of ways to describe and explain.  Contrary to the restrictions of positivists, scientists practice science the way they feel is most effective, and most modern theories include unobservable entities (photons, electrons,...) and interactions (electrical fields and forces,...) among their essential components.  Although scientists sometimes generate and utilize a theory that is limited to a description of empirical patterns, usually this type of theory is seen as a temporary stage along the path to a more complete theory that probably will include unobservable components.  This feeling, that "we're not there yet" when we have only a descriptive theory for an empirical pattern, contrasts with the positivist view that this should be the logical ending point for science.
    For example, according to a prominent contemporary defender of positivism (empiricism), a theory should be only a way to conveniently summarize a large amount of data, to make generalizations about observable quantities, and to make predictions:
To develop an empiricist [positivist] account of science is to depict it as involving a search for truth only about the empirical world, about what is actual and observable. ...  [This positivist account] must involve throughout a resolute rejection of the demand for an explanation of the regularities in the observable course of nature, by means of truths concerning a reality beyond what is actual and observable, as a demand which plays no role in the scientific enterprise.  (van Fraassen, 1980, pp. 202-203)
A "positivist account" is a philosophical theory about what scientists should do and, more important, what they should not do, rather than a description of what scientists actually do.  It is prescriptive, not descriptive.  When van Fraassen states that in a positivist account "the demand for an explanation... plays no role in the scientific enterprise," the meaning would be more clear if he claimed that "according to positivist views of science, the demand for an explanation... should play no role in the scientific enterprise."
    But if scientists "do what they should" (according to positivism) they will operate at a disadvantage compared with scientists who misbehave, because most of the best modern theories are non-positivist.  Faced with this choice, to either "behave as they should" or be effective, most scientists will choose freedom and effectiveness.

    { Since modern versions of positivism can be called empiricism, in an effort to avoid confusion I'll call attention to an important difference between two similar terms:  empirical science, which uses empirical observations and empirical evaluations, includes all science, both empiricist science (with only observable components in theories) and non-empiricist science (that allows both observable and unobservable components).  Since HD logic allows scientists to empirically evaluate the plausibility of components that cannot be observed (but that produce effects which can be observed), non-empiricist science (which can include theories containing non-observable components) requires HD logic.  But empiricist science (i.e., positivist science) can be done with or without HD;  or, viewed from another perspective, HD logic can be done for theories with observable and/or unobservable components.  In fact, a desire to accomodate non-positivist theories in science was a major motivation in developing the current importance of HD logic. }

Here is part of the section on positivism from my "Details of Scientific Method" page:

CONSTRAINTS ON UNOBSERVABLE COMPONENTS.   A positivist believes that scientific theories should not postulate the existence of unobservable entities, actions, or interactions.  For example, behaviorist psychology avoids the concept of "thinking" because it cannot be directly observed.  A strict positivist will applaud Newton's theory of gravitation, despite its lack of a causal explanatory mechanism, because it is an empirical generalization that is reliable and approximately accurate, and it does not postulate (as do more recent theories of gravity) unobservable entities such as fields, curved space, or gravitons.  But most scientists, although they appreciate Newton's descriptive theory for what it is, consider the absence of explanation to be a weakness.
    some comments about terminology:  Positivism was proposed in the 1830s by Auguste Comte, who was motivated partly by anti-religious ideology.  In the early 20th century a philosophy of logical positivism was developed to combine positivism with other ideas.  In current use, "positivism" can be used in a narrow sense (as Comte did, and as I do here) or it can refer to anything connected with logical positivism, including the "other ideas" and more.  Logical positivism can also be called logical empiricism.  { Notice that empiricism (i.e., positivism) is not the same as empirical.  A theory that is non-empiricist (because it some components, such as atoms or molecules, that are unobservable) can make predictions about empirical data that can be used in empirical evaluation. }
    Although positivism (or empiricism, the name typically given to the modern versions of positivism currently being proposed) is considered a legitimate perspective in philosophy, it is rare among scientists, who welcome a wide variety of ways to describe and explain.  Many modern theories include unobservable entities and actions, such as electrons and electromagnetic force, among their essential components.  Although most scientists welcome a descriptive theory that only describes empirical patterns, at this point they think "we're not there yet" because their limited theory is seen as just a temporary stage along the path to a more complete theory.  This attitude contrasts with the positivist view that a descriptive theory should be the ending point for science.
    The ISM framework includes two types of theories (and corresponding models) — descriptive and explanatory — so it is compatible with any type of scientific theory, whether it is descriptive, explanatory, or has some characteristics of each.  My own anti-positivist opinions, which are not part of the ISM framework, are summarized in the preceding paragraph, and are discussed in more depth on the EKS-RATED page. [i.e., in the section you've been reading]

 
Summaries
Table of Contents


To check any of the REFERENCES in this page, click here and a page with references for the whole website (but mainly for this page and for "Details of Scientific Method") will open in a new window.



 
This website for Whole-Person Education has TWO KINDS OF LINKS:
an ITALICIZED LINK keeps you inside a page, moving you to another part of it, and
 a NON-ITALICIZED LINK opens another page.  Both keep everything inside this window, 
so your browser's BACK-button will always take you back to where you were.
 

OTHER PAGES:
If you like this page, you may also like the following related pages:

CULTURAL-PERSONAL FACTORS IN SCIENCE

IDEALIZATIONS and RANGE DIAGRAMS

GOALS — IS THERE A SCIENTIFIC METHOD?

TERMS (COPING WITH CONFUSION)

SCIENCE AND DESIGN (similarities, differences,...)

DETAILS OF SCIENTIFIC METHOD
When you click the link above, the large
"Detailed Examination of Scientific Method"
will open in its own separate new window.
Then both pages (EKS-Rated and Details) will be open
so you can quickly move back and forth between them.
Then you can move to a specific location inside
the Details-page by replacing #top (at the
end of the URL) with another suffix.
Which suffix?  Here are some interesting options:
( re: predictive contrast and "so what", add #contrast )
( re: theories used to interpret observations, add #supp )
( re: statistical conclusions, add #agree )
( re: the utility of simplified models, add #oversimp )
( re: variable-strength hypotheses, add #hyp )
( re: unobservable entities in theories, add #emp )
( re: descriptive and explanatory theories, add #theory )


• a sitemap for Thinking Skills in Education:
Scientific Method, Problem Solving, and Design Method

A Grand Tour of Learning, Teaching, Thinking
This is an overview of my ideas about education,
with tips for "what to do next" after reading
each of three introductory pages:

Motivations (and strategies) for Learning
goal-directed personal motives for learning;  teamwork;
how a friend learned to weld, and how I didn't learn to ski

Aesop's Activities for Goal-Directed Education
a creative coordinating of goals and activities will
help students gain experience and learn from it

An Introduction to Design Method
how to design a product, strategy, or theory
(this includes almost everything we do in life!)


  This area of Thinking Skills has sub-areas of 
 Productive Thinking (Skills and Methods) 
Creative Thinking in Education       Critical Thinking in Education 

   
this page is
http://www.asa3.org/ASA/education/science/eks.htm

copyright © 1997 by Craig Rusbult, all rights reserved
 


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