Nichols, Physics Envy

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OUTGROWING PHYSICS ENVY:RECONCEPTUALIZING SOCIALRESEARCHDavid P. Nichols

ABSTRACT: There is a pervasive sense of unease among social sci-entists concerning the status of social research. This unease is rootedpartly in a false dichotomy between objectivity and subjectivity and abelief that an idealized positivist version of classical physics shouldbe the model for all sciences. Experimental methodology is one ofmany valid ways of obtaining knowledge and carries with its use aparticular set of problems, particularly when social phenomena arestudied. A reconceptualization of social research is needed, in whichexperimental and quasi-experimental methods are used with morecaution and are supplemented by a more thorough conceptual appa-ratus .

What are appropriate goals and methods for research in the so-cial sciences? The fact that this question does not have obvious an-swers for many social scientists is borne out by the existence of twoedited volumes produced as the result of conferences at the Univer-sity of Chicago, in 1979 (Kruskal, 1982) and 1983 (Fiske & Shweder,1986). The range of opinions expressed in these volumes is demonstra-tive of the deep divisions that exist in the social science communityover basic issues.

David P. Nichols, AM, University of Chicago, Department of Psychology, Commit-tee on Research Methodology and Quantitative Psychology, also is with SPSS, Inc.,Chicago, IL. Reprint requests should he addressed to the author at SPSS Inc., 444 N.Michigan A venue, Chicago, IL 60611.ContemporaryFamily Therapy, 15(1). February 1993O 1993 Human Sciences Press, Inc. 5 1


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THE CURRENT STATUS OF SOCIAL RESEARCH:A PERVASIVE SENSE OF UNEASETexts' such as K erlinge r (1964) and Bock (1975) presented viewsof social scientific research firmly rooted in the paradigm of logicalpositivism. According to Kerlinger, "Scientific research is systematic,controlled, empirical, and critical investigation of hjrpothetical propo-sit ions about the presumed relations among natural phenomena" (p.13). The hypothetico-deductive framework borrowed from classicalphysics has long been seen by many as the key to the building of asuccessful social science, a physics of social phenomena.However, the idealized v ersion of science presen ted by t he logicalpositivists has been under siege for several decades, due to eventsboth internal and external to research in modem physics. The inter-nal events center around relativity and, even more importantly, theradical uncertainties introduced by quantum mechanics (Capra, 1975,

1982). Shweder (1986) views this as an important lesson for socialscience. "It is perhaps worth noting that modem physics, since atleast the work of Niels Bohr, has moved away from mechanistic imag-ery and the idea of objective predetermination and toward what hasaptly been labeled the physics of possibility, ambiguity, and uncer-tainty" (p. 175).Nevertheless, perceptions of physics and science have remainedstatic in many quarters. "It would seem that our mj^hic idealizationsof science change quite slowly" (Shweder, 1986, p. 175). Part of thereason for the slow evolution of ideas about how science works is thatthe people who choose to pursue careers in the physical and naturalsciences are not predisposed to challenging the dominant idealization.As Harding (1991) puts it, "given the qualities that make them 'good

scientists, ' natural scientists are the last people to suppose it desir-.able to examine the l imits of their minds to mirror nature or makerational scientific choices, and of their wills to bring about theirchoices" (p. 95). This makes them "psychologically the wrong peopleto provide causal accounts of science" (p. 95).According to Harding, a better understanding of science can begained by the application of social theoretic skills to the natural sci-entific en terprise . "Wha t is needed are people traine d in critical socialtheory: that is, in locating the social contextspsychological, histori-cal, sociological, political, economicthat give meanin g an d power tohistorical actors, their ideas, and their audiences" (p. 95). Harding's


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thesis is that the idealized model of physics not only is not a goodmodel for the social sciences, but that it is not even a good model forphysics.Harding's work points to the fact that some of the same kind ofquestioning of basic principles and assimiptions that is taking placein the social sciences is also occurring in the natural sciences. Muchof the controversy was prompted by the publication in 1962 ofThomas Kuhn's The Structure of Scientific Revolutions. This bomb-shell from an historian of science was the external complement to theevents in modem physics previously discussed. Kuhn's challenge toconventional views of scientific progress was profound enough to beentertained most seriously by some of the world's most prominentphilosophers and historians of science. A 1965 London symposium onKuhn's ideas produced a volume (Lakatos & Musgrave, 1970) thatmatches the later social science volumes in the variety of expressedperspectives.It is safe to say that the positivist conception of scientific progressstill reigns among the majority of physical scientists. While also amajor force among social scientists, belief in the search for a physicsof social phenomena is no longer near universal. As Cronbach (1986,pp . 84-85) expla ins,A "social physics" is an unlikely development. The Pill datesback less than one generation; widespread advanced educa-tion of women dates back less than two; about four genera-tions back in Western democracies, free public educationspread; five generations back, the Industrial Revolution.Such rapid change severely limits generalization about socialstructures and relationships.This sentiment is echoed by D'Andrade (1986), who criticizes theapplication of the covering law model of classical physics to the sub-ject matter of the social sciences. "A more adequate model wouldstress that the way the generalizations develop in any domain shouldbe appropriate to the kinds of order and regularity found in that do-ma in" (p. 26). Since social phenom ena do not display th e sam e kind oforder or regularity found in physical phenomena, the search for thesame level of fundamental laws makes little sense, and the relativelack of generality of the descriptions and explanations to be found insocial scientific accounts should not be seen as evidence of a lack of


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progress, but rather as an accurate refiection of the status of the sub-ject matter.Both Cronbach and D'Andrade see the norms of progress found inth e physic al sciences Eis inap pro pria te for the social sciences beca useof the real nature of the phenomena found in the social arena. Thereare those (e.g., Gerge n, 1985, 1986) who go even farth er, deny ing th ereality of social phenomena independent of our descriptions, or con-structions.

Social actions, as ma tter s of common concern, owe their exis-tence to the social process whereby meanings are generatedand events indexed by these meanings. There are no inde-pendently identifiable, real-world referents to which the lan-guage of social description is cemented (1986, p. 143).Though we may thin k th at we construct theories to describe realevents, and may therefore at t imes alter our theories because theyfail to express the nature of the social world, according to Grergen, "inthe case of describing human action, we confront the possibility thattheory is fundamentally closed to empirical evaluation" (p. 159). Theresult is tha t ra ther tha n accum ulating knowledge about how the worldworks, "the sciences [should] chiefly be viewed as sources of intel-ligibility or vehicles for the conceptual construction of reality" (p. 159).

THE ROOTS OF OUR DISCONTENT:ABSOLU TISM AND A FALS E DICHOTOMY

Gergen's position represents the opposite side of a dichotomyformed w ith th e trad ition al p osition of logical positivism. Th is opposi-tion between objectivism and relativism was appealingly laid out inPirsig 's (1974) Zen a nd the Art of Motorcycle Maintenance in the formof a dilemma posed to the protagonist. The importance and pervasiv-ness of this dichotomy are hard to overstate. As Bernstein (1983)says, it is "the c entral cultu ral opposition of our tim e" (p. 7).

Bernstein sums up the standard view of the positivist or objecti-vist to the relativist argument: "One cannot consistently state thecase for relativism without undermining it" (p. 9). In other words, thestatement that everjrthing is relative is itself an absolute statementand is therefore logically self-refuting. T his response is, however, toopat and too easy. This is so because the objectivist position begins by


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assuming the rules of logic; the game has been rigged from the start.The onus of responsibility for establishing basic assumptions hasbeen placed on the relativist, and he or she will surely fail underthese rules. However, should we reverse the responsibility by refus-ing to assum e th e rules of logic, the position of the objectivist will fareno better.This is so because no system of thought is capable offiiUy ustify-ing its own assumptions. As Lakatos (1970) puts it, "All scientificresearch programmes m ay be characterized by their 'hard core'. Thenegative heuristic of the programme forbids us to direct the modustollens at this 'hard core"' (p. 133). This hard core "is 'irrefiitable bythe methodological decision of its protagonists" (p. 135). For logic, apart of the hard core is the existence of Absolute Truth. Pirsig (1974)illustrates the resulting fundamental problem with the example ofthe Socratic method: "Once it's stated that 'the dialectic comes beforeanj^thing else,' this statement itself becomes a dialectical entity, sub-ject to dialectical question" (p. 353).The assumption that formal logical principles are the basis of allscientific thought is so deeply ingrained in modem western culturetha t the way out of this dilemma may be unclear to many scientists.As Shweder (1986) says, "the mythic idealization in our culture of thephysical or natural sciences may have led us to draw an all-too-sharpcontrast between what is hard and what is soft, between what is ob-jective and what is subjective" (p. 175). In other words, it may not bethe case that one either accepts the existence of Absolute Truth orelse winds up accepting the idea that all views have equal claims tovalidity and one therefore cannot with justification argue against anyperspective.This point is by no means a new one. Bernstein (1976, 1983),Hubner (1983), Laudan (1984), Pirsig (1974), Rorty (1979), Shweder(1986), and Toulmin (1972) all explicitly make this claim. What isimportant to understand is that the problems involved in the adher-ence to this dichotomy stem from the fact that the objectivist andrelativist positions are actually both sides of the same coinan abso-lutist interpretation of nature that has troubled us for centuries. AsBernstein (1983) puts it, "Relativism ultimately makes sense (andgains its plausibility) as the dialectical an tithes is to ohjectivism. If wesee through objectivism, if we expose what is wrong with this way ofthinking, then we are at the same time questioning the very intel-ligibility of relativism" (p. 167).


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BEYOND THE FALSE DICHOTOMYThe way out of the dilemm a begins with the realization th at "in-

ductive and deductive logic cannot account for every example of sys-tematic, constrained thinking, and there are many examples of im-personal constraints th at are not logical rulesnot the least of whichare the rules of language" (Shweder, 1986, p. 179). In Toulmin's(1972) words, we must "abandon . . . the philosophers' tradition al as-sumption that rationality is a sub-species of logicality" (p. 486). If we"reject the commitment to logical systematicity which makes absolut-ism and relativism appear the only altematives available" (p. 84) wewill find that "it is still possible to steer a middle way between theabsolutist and relativist extremes" (p. 497).Shweder's (1986, pp. 177-178) discussion of this third way isworth quoting at length:There is, however, a third rea ction to th at idealization of ob-jective science discussed earlier. I will call it the science-of-subjectivity reaction, even though the expression 'science ofsubjectivity' is a contradiction in terms from the perspectiveof either hermeneutics or positivism. The basic idea is thatwe must revise our conception of the relationship betweennature and culture, objectivity and subjectivity. The idea isthat as we have learned more from historians and histori-cally oriented philosophers about the actual workings of sci-ence . . . objectivity-seeking science has come to seem inher-ently subject dependent. And, as we have learned more fromlinguists, sociologists, anthropologists, and psychologistsabout the workings of subjectivity . . . human subjectivityhas come to seem more objectlike than imagined. The realworld, it seems, is populated with subject-dependent objectsand objectlike subjectivity, two types of phenom ena for wh ichthere is no place in the mutually exclusive and exhaustiverealms of the symbol-and-meaning-seeking herm eneuticistand the automated-law-seeking positivist.

One basic implication of this view for social research is that "There isa soft side to all hard data, or perhaps the crucial point is that with-out the soft side there is no hard side" (p. 174).For those engaged in research centered on issues of rationality,the implications are perhaps even more profound: "other conceptionsthat rest on a neat and clean contrast between what's objective and


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what's subjective ought to be revised, which means, to say the least,we may have to rethink for a bit our conception of 'rationality' andour concept of'meaning'" (p. 178). Echoing Pirsig's (1974) belief that"reason may be expanded to include elements that have previouslybeen unassimilable and thus have been considered irrational" (p.230), Shweder (1986) reminds us that "A science of subjectivity re-quire s a broadened conception of ratio nality " (p. 178).

Shweder's version of a science of subjectivity fits in well withqualitative research traditions in the social sciences, particularlythose emanating from anthropology. Given my background in moretradit ional quantitative methods, rather than discussing the conductof qua litative resea rch, I feel more comfortable discussing some of thepitfalls and limitations of quantitative social research that make thequalitat ive approach an important complement.

SCIENCE AS CONDUCTED BY MORTALSThe tra dition al p ositiyist conception of science obscures a nu mb erof important elements of scientific endeavor. One major fiaw of thisconception is the failure to realize that science never has been andneve r could be value free or value ne utra l (Hard ing, 1986, 1991). Per-haps to some social scientists this realization is commonplace. How-ever, a simple list of the rather obvious uses of dubious "objectivescientific facts" to argue for the inevitability of inequitable social andeconomic institutions would comprise more space than this paper per-mits . Skeptics are referred to Bayer (1981), Fausto-Sterling (1985),Gould (1981), Kamin (1981), Lewontin, Rose & Kamin (1984), Mar-mor, Mashow, & Harvey (1990), Mensh & Mensh (1991), Orfield &Ashkinaze (1991), Ryan (1971), Schiff & Lewontin (1986), Schwartz(1986), Schwarz (1988), and Tuana (1989) for a small sampling of theways in which class, gender and race based arguments for superiorityand/or privelege are couched in terms of so-called objective science. Apar ticula rly profound an alysis of the transfo rmation of political econ-omy into economic science via removal of the moral dimension is pro-vided by Lux (1990).Though prejudices, power politics, and assumptions play majorroles in all forms of science, they are particularly pronounced in so-cial researc h. The relative lack of prestige enjoyed by social scien tistsas compared with physical scientists stems partly from the fact thatsocial reseEirch is generally more directly connected to everyday life.


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and is therefore more accessible to non scientists. Few people hav e anopinion about quarks; everyone has an opinion about abortion or so-cial welfare policy. Research in the social sciences proceeds undermuch closer scutiny by the public, and with much more expected,than does natural scientific resejirch. When I say more is expected, Imean that in general people have more emotion invested in the find-ings of social research than they do in physical science research. Rich-ter (1986, p. 285) notes the im plications:Once one recognizes tha t measures of success, in the absenceof an absolute standard, are socially negotiated quantities, aspecial disadvantage of the social sciences becomes clear. Thescientific fields that can most easily claim to be successfulare those in which the measures of success are internalized,sometimes even self-fulfilling. Astronomy defines the mea-sures of success and succeeds. The social sciences, in con-trast, are often faced with measures of success beyond theircontrol. In many cases, the larger society defines the rele-vant problems for the social sciences and has strong preju-dices as to what constitutes an acceptable answer. This ex-ternalized valuation system seems to be a source of much ofthe present unease in the social sciences.The treatmen ts of the status of social science by Cronbach (1982,1986), D'Andrade (1986), Gergen (1985, 1986) and Shweder (1986),among others, are attempts to begin a renegotiation of the expecta-tions for social research. Though some (e.g., Gergen) would seem toprefer to reverse the traditional roles and set the social sciences up inthe position of lecturer, Richter and others point to the benefits of amore symmetric dialogue. Critical study of the conduct of physical

and natural sciences has much to offer social scientists. The impor-tan t point is to make this study truly critical, to avoid the extremes ofpretending that these fields offer us nothing of relevance or that theyestablish valid norm s of success tha t we can hope to approach only byslavishly mimicking their methods.EXPERIMENTAL METHODOLOGY ASA SET OF HEURISTICS

An excellent example of the potential of this attitude is providedby Wimsatt (1986) in his study of heuristic strategies. Though muchof his paper centers on biological topics, there is much here to be


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learned relevan t to social research without denying the differences ofthe biological and social domains. Heuristics are particularly impor-tant in the study of social phenomena because they are ubiquitous.Indeed, the term heuristic originated among researchers of humanthought.Heuristics are strategies for problem solving (in any formal orinformal domain) tha t are characterized according to Wimsatt by fourprimary features. First, they differ from the traditional deductivemodel of problem solving strategies in that they do not guaranteecorrect solutions. In other words, unlike an algorithm, given validinput and a correctly applied heuristic, invalid conclusions may re-sult. Second, heuristics are nonetheless widely used because they areeasier to produce and apply than are perfect solutions. Third, whenthey fail, they do so in systematic ways, due to the biases in theirsimplifying assumptions. These biases lead to systematic errors incertain classes of problems. Finally, application of an heuristic to aproblem alters or reformulates the question asked to a different butintuitively related one. The important implication here is that an-swers to the new problem may not be answers to the original one.

Among the interesting phenomena that can be at least partlycharacterized as heuristics are biological, psychological, and socialadap tations . Much of the focus of Wim satt's analysis is on th e reduc-tionist biases prevalent in population genetic research on the units ofselection controversy. The relevance of his discussion to concerns ofthose who see social phenomena as often being unnaturally reducedto collections of individual actors is made obvious by Wimsatt's com-me nts about what he te rms perceptual focus: "If groups are thought ofas merely 'collections of individuals,' . . . then the description of pro-cesses is referred to the individual level, and one cannot see that as-sumptions that appear benign at that level may be dangerous over-simplifications when viewed at a higher level" (p. 305).The complexity of the social world overwhelms us. We are notLaplacean demons, so we have to adopt some strategies for dealingwith th e m ass of available information. We must select certain thingsto pay attention to and others to ignore. Our biological endowmenthas provided us with some heuristic devices in the form of senses.Social and cultural institutions provide us with others. In the subcul-ture of traditional western science, the experimental method is an-other important heuristic.Experimental methodology comprises a powerful set of heuristicsthat can be very useful when its assumptions are met. However, the


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power comes in exchange for a monumental assumption when weseek to establish causal relationships. This assumption is that we canma nipu late at will all of the c ausal factors, so as to be able to produceall possible combinations (though we sometimes employ only a ran-dom sample of them). When we choose not to vary some factors wemust be aware that we have reframed the general causal questionand that linkages established at one level of a causal factor must beassumed conditional upon that state. Cronbach (1982) provides an ex-cellent brief sum ma ry of some of the erro rs tha t can result from n aiveuse of the experimental method in social research.Experimental methods also assume that we have the power torandomly assign units of analysis to different treatment conditions.Unfortunately, social scientists often do not have the ability to ran-domly assign participants to conditions. We are often forced to dealwith preselected units because this is the way things work in thedomains we wish to study. If we insist on random assignment, we

often introduce another problem: our randomly assigned conditionsare not representative of the conditions to which we wish to makeinferences. As Cronbach says, "randomization almost always comes atthe expense of representativeness" (p. 64). Though we may get volun-teers to consent to randomly selected therapeutic modalities for pur-poses of a study, we cannot make people live this way in the world atlarge.People do not live in laboratories. Attempting to replace thequestion of what happens in the social world with what happens in acontrived experimental situation is an extremely hizardous thing todo . Even when we are lucky enoug h to be able to sufficiently approxi-mate controlled conditions long enough to study a particular set ofinteractions in a particular context, we are oflen frustrated when weattempt to transport these findings to other contexts. As Cronbachputs it, "Social knowledge is used in circumstances other than thoseoriginally studied. New sites and new clienteles have to be served,and the original site changes with time. Extrapolation is speculativeeven when the effect is established beyond question in the originalcontext" (p. 66).Of course most social research in the experimental tradition isactually wh at is known as quasi-experimental (Cook & Campbell, 1979)because we are explicitly aware of our inability to control some poten-tially major causal factors. Though we have at our disposal a variety ofstatistical tools that we can use in order to attempt to account for thesefactors, the effort is a perilous one. Cronbach notes (p. 66).


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Disregarding of causally relevant conditions is inherent inall the time-hallowed invocations of ceteris paribus. Post hocmatching, partialing, and covariance adjustment try to tellus what relations would be if we could wipe out certain cor-relations of background factors with events. In evaluations oftreatments, these adjustments seek to describe a counterfac-tual world in which initial characteristics of persons do notinfluence the tre atm ent they get . . . To create such a worldwould require intervention radical enough to denature thet reatment .

In sum, all other things g enerally are never equal when dealing w ithsocial processes.One of the most common frustrations of social researchers is thefailure of effects established in one context to replicate in other con-texts. This lack of generalizability of effects is a major part of thereason for the belief of some scientists that the social sciences havenot made substantial progress. A large part of this problem is due tothe use of causal reasoning that places an emphasis on particularevents at the expense of broader conditions. Cronbach (1982) notesthat "An event in a community is likely to interact with other fea-tures of the social scene. For students of an innovation to speak of aneffect 'of the treatment' is therefore shortsighted. The circumstancessurroimding the intervention are part of the cause" (pp. 66-67).

Given that a number of conditions Eire associated with a particu-lar outcome, the selection of a small subset of these as the importantcausal factor(s) is an heuristic device. In the case of most causalthinking in science and the everyday world, the bias in this heuristictends strongly toward choosing as small a number of "causes" as pos-sible (often only one) and to select these from among the unusualfeatures of the situation; that is, to ignore that which is normal andordinary. Though very common, this is by no means generally justi-fiable (Salmon, 1984). To Cronbach "The asjnnmetric em phasis on th etreatment as the cause, rather than on the combination of treatment,units, setting, and so on, arises from the intent of social scientists toaid in the manipulation of human affairs" (1986, p. 94).

STATISTICAL CONTROLS AND THE SELECTIVITYOF SOCIAL PR OCESSESWe have seen that the direct application of the pure experimen-tal method to most social research is impossible; quasi-experimental


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methods are th us thought to be the next best thing. If we can't controlall the important factors directly, we can at least control those of in-terest directly and control for others statistically, or so the reasoninggoes. In other cases we look to "natural experiments," where changesin purported causes of interest happen without our intervention, andagain attempt to control for nuisance factors through statistical con-trols. But just how valid is this reliance on statistical control? In amonograph that should be required reading for all students of socialprocesses, Lieberson (1985, p. 19) demonstrates that this approach isfi-aught with peril.What is wrong with this procedure? If there is any feature ofsocial life about which a high degree of confidence exists, itwould be th is simple principle: social processes are selectiveprocesses. As a consequence, the reason for taking into ac-count the differences found between the populations is alsothe very same reason for doubting whether such efforts canbe successful very often. For selective processes are probablyoperating within the control variables themselves.Most social scientists, if asked, would say that the application ofcontrol variables in quasi-experimental or field research is at worstbenign, and generally to be required. As Lieberson shows however,this belief is based on mistaken assumptions about the effects of con-trol variables in the presence of unmeasured selectivity. The conse-quences of applying the control method "are quite contary to the stan-dard assumptions in social research. Under some conditions, theapplication of controls generates results that are actually farther re-moved from the truth than would occur if no controls were applied

whatsoever" (p. 22).This problem, tha t applying controls is not guaranteed to be help-ful, or even benign, is not linked to the use of any specific statisticalprocedures, but results from a more fundamental problem: withoutknowing the reasons for the interrelationships among the indepen-dent variab les in a functional model, we have no way of knowing th eimplications of applying controls. Controls can only be assumed to bebenign when they have no effect on the apparent relationship be-tween the independent and dependent variables. Thus when they a reof the most potential usefulness, they are also the most dangerous.One of the m eiinstays of the scientific enterprise is replication. I tis widely assumed that if a causal relationship exists, repeated


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studies will confirm it. Unfortunately, this is not necessarily the case.According to Lieberson, replication won't always tell us what's realand what's chance or artifact because unmeasured selective forceswill often differ across contexts and replications and thus produce dif-ferent results . "Fur ther test s, follow-up studies, newer statistica l pro-cedures, exchanges in the journals, bigger samples, more controls,and the like, may or may not support the original conclusion, but itdoes not really matter if they are all based on the same underlyingfalse premise" (p. 39).Even the latest and greatest of the super statistical methods suchas struc tural equation modeling are not up to the task in the presenceof unmeasured selective processes. The current rage for such modelsbelies the fact that the concept of path models has been around formore tha n 70 years (see Wright, 1921) without solving the basic prob-lems associated with drawing causal inferences from associations orcorrelations. Firm causal inference comes from theory and design, notfrom statistics. As Cronbach (1982) says, "These advances should in-crease the yield from field data, but I cannot share the optimism thatsuperadjustments will warra nt causal conclusions. Curve fitting can-not lift us into orbit unless fueled by substantive insight" (p. 67).

OTHER DANGERS INQUASI-EXPERIMENTAL RESEARCH:CONTAMINATION, ASYMMETRY ANDLEVELS OF ANALYSISAt the risk of some redundancy, I think it is important to sum-marize further points made by Lieberson (1985). He lists four other

problems that haunt quasi-experimental research. These by no meansexhaust the threats to validity of quasi-experimental research (seeCook & Campbell, 1979), but considered in conjunction with the selec-tivity issue they provide a powerful argument for the need to recon-ceptualize traditional quantitative social scientific research meth-odology.The first hazard, contamination, occurs when the presence of orchange in an independent variable has effects where it is not presentor does not change. Examples would be the impact of tax laws orprofessional licensure requ irements in some jurisdictions on the be-havior of governing bodies or professionals in other places. Effects ofthe measures on behavior within the original jurisdictions would not


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be ascertetinable by comparison with areas without the measures, be-cause the baseline areas have also been affected.The second problem is that of asymmetric causality. In general,social researchers assume that changes in a dependent variable re-sulting from changes in one direction of an independent variable canbe reversed by moving the independent variable back to the originalstate. However, this is quite often not the case with social processes.For example, the conditions which give rise to social movements canand often do change without the social movements disappearing. Pro-cesses tend to take on a life of thei r own once set in motion, and oftenCin be only partially reversed if at all.The third issue is the confusion of proper level of analysis or theassumption that processes functioning in a certain manner at onelevel will function analogously at another level. The most commonversion occurs when reductionist assumptions are made, as discussedby Wimsatt (1986), and systemic properties are ignored in favor ofconcentration on individual parts of a system. A great deal of psycho-logical theory and research falls prey to the fallacious assumptionthat social processes can be accounted for by studying isolated indi-viduals. The field of family therapy is in large part a result of therealization that humans as social beings exist within larger socialsystems, the family being a crucial one.

ANALY SIS OF VARIATION AN DANALYSIS OF CAUSES

The fourth issue, that of the role of variation in causal and statis-tical analysis, is so important and so widely misunderstood as to war-rant extensive attention. As anyone who has had an introductorycourse in statistics knows, statistical methods cannot be appliedwhere variation does not exist. The almost universal requirem ent inempirical social research to apply statistical methods if one wishes tohave work seriously considered has important implications for ourselection of research problems and our conceptualization of causalprocesses. As Lieberson says, "one must ask whether problems aresometimes posed in a certain way more because they meet statisticalcriteria and needs than because they are the most appropriate re-search question in terms of either substantive or theoretical issues"(p. 89).He goes on to point out that issues of variability should be sec-ondary to more basic issues of underlying causal forces.


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It is prem ature to think about variability in an ev ent beforeknowledge is developed about the fundemiental cause of theevent itself Explanation of a variable's variation should notbe confused with an explanation of the event or process itself.Contrary to the assumption commonly made in social re-search, we cannot learn the fundamental cause of an eventby studying the factors affecting its variation ; at best, we canonly learn how secondary characteristics might modify theconsequences of a fundamental cause (p. 115).Choosing research problems focused on accounting for variation in avariable of interest will not necessarily lead to knowledge about fun-damental causes because "there is no intrinsic reason for expectingthe properties of the system to be logically deduced from observingvariation in the behavior of the individual units" (p. 116).Standard reporting of research results often centers around theattribution of variation in the dependent variable as being explainedby variation in one or more independent variables. However, the as-sumed implications of the observed associations are often (if not al-ways) in error.

It is erroneous to assume that the importance of causalforcesin eithe r an absolute or relative sensecan be deter-mined by the amount of variation "explained" by them insome empirical study. The variance and range of both thedependent variable and the independent variables will al-most certainly vary from setting to setting, and in turn thiswill affect the relative importance attributed to each inde-pendent variable (p. 117).Contrary to the assumption underlying most empirical social re-search, "The analysis of differences or variability is an analysis ofjust thatit is not to be confused with the analysis of causes, espe-cially those that are so widespread that they help explain very littleof the variation" (p. 119). These same points are also well illustratedby Lewontin (1974).The fiaw in current practice is due I think not so much to thebasic underlying causal model as to the assumptions made about theapplicability of the model in practice. That is, the model being as-sumed says that if we could look at the state of the dependent vari-able of interest under all possible combinations of states of the caus-ally relevant factors, we would be able to associate a particular state(under a deterministic model) or distribution of states (under a proba-


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bilistic model) with each combination of factors. Under such circum-stances of omniscience, we could thus determine all the possible vari-ations in states of the dependent variable and how they are linkedwith combinations of the causal factors.The error occurs when we make one of two assumptions aboutour ability to infer from observed combinations of factors. The moregeneral assumption is that we can in essence infer the entire causalsystem from the nonrandom subset that we observe. This assumptionis always incorrect and not likely to be defended for long by those towhom it is accurately portrayed. The more common case is to assumethat we can at least infer from the observed combinations to thelarger subset of plausibly produceable combinations. While morelikely to be defended than the more general assumption, the underly-ing logic is the same and therefore similarly fallacious.As Cronbach (1982) was quoted as saying earlier, our desire tointervene in human affairs leads to an asymmetric focus on that

which we deliberately manipulate, pushing off as background the set-ting or context within which our manipulations occur. However, as healso says, these conditions are just as much a part of the cause of aparticular outcome as are the "treatments" we apply. Should we findways of varying these "background" constants, we can produce differ-ent outcomes.I have spent so much time on this problem because I believe thatthis erroneous approach to und erstanding causal relationships is ex-tremely widespread among social scientists. As evidence I offer thefollowing passage from an article discussing the relative importanceof genes and environment for a variety of behaviors (Plomin, 1989).Note how the focus on a ttempting to account for differences in behav-iors via differences in causal factors produces a completely nonsensi-cal statem ent:

The importance of nonshared environmental factors suggeststhe need for a reconceptualization of environmental influ-ences that focuses on experiential differences between chil-dren in the same family. That is, many environmental fac-tors differ across families; these include socioeconomicstatus, p arental education, and childrearing practices. How-ever, to the extent that these environmental factors do not dif-fer between children growing up in the same family, they dono t influence behavioral development [italics added]. The crit-ical question becomes, Why are children in the same familyso different from one another? The key to unlock this riddleis to study more than one child per family. This permits the


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study of experiential differences within a family and theirassociation with differences in outcome (p. 109).The mistake here of course is the belief that because we cannotassociate differences in a factor with differences in an outcome, thefactor plays no part in the outcome. This expresses itself in the ital-icized statement above, the obviously erroneous logic of which infersthat any treatment, however profound, that is applied identically toall of the children in a family will have no effect on their behavioraldevelopment.Here we have methodology dictating theory, producing truly ab-surd results. What is worse is that this article appeared in a specialchild development issue of the widely read American Psychologist,and produced no comment (at least none that was published) concern-ing this fundamental logical blunder. It would appear that the fallacyof explaining events only through observed variations, while ignoring

observed constants that could vary and would produce different re-sults if they did vary, is widespread among far more social scientiststhan I would have hoped (unless of course a great many people alsonoticed this and decided it was not worthy of a response, or as I did,decided to see if anyone else noticed it). I had long feared this, butnever expected such a graphic illustration.

WHITHER VALID QUANTITATIVESOCIAL RESEARCH?So far we have seen an overwhelming arra y of thr eat s to the val-idity of quan titative social research (some of these are of course rele-

vant to broader classes of research methodology). Are we forced tosurrender and simply give up on quantitative social research? I don'tthink so. As Lieberson (1985) says, "a rigorous science of society is anenterprise that is well worth pursuing. The goal is not to show thatsocial science is intrinsically unobtainable. Rather, it is to eliminatethe unthinking imitation of a crude physical science model that char-acterizes so much of social research" (pp. 171-172).Some obvious implications are that we should not pretend thatwe have the equivalent of controlled experimental conditions whenwe do not, or tha t context specific relationships are con text free. Thismeans that many current research programs should be reconcep-tualized as exploratory and descriptive, rather than confirmatory.There is nothing wrong with th is; accurate description, both q ualita-


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tive and quantitative, is exceedingly important in any scientific pro-gram, and contrsuy to popular opinion, we do not have to do experi-ments to be doing science. To practice science relevant to society re-quires moving beyond the constricting bounds of the hypothetico-deductive framework. "To grapple with loosely bounded problemsthat is, with almost any problem that connects up with communityconcernswe need to blur the lines that separate 'values' from 'facts,''humanities' from 'sciences,' and 'quantitative' from 'qualitative' or'applied' from 'basic' research" (Cronbach, 1986, p. 102).Another recommendation Lieberson makes is to look more care-fully for what he calls transformational causal principlesbasiccauses that produce the same outcomes under a wide variety of condi-tions. This is obviously much more easily said than done, but as wehave seen, the current method of trying to derive the basic causalmechanisms from observed associations in particular contexts doesnot offer much hope. Lieberson believes this to be due to the fact tha twe are looking at superficial linkages that often change while basiccausal principles do not.His most importan t suggestion is "a shift in focus from the depen-dent variab le to the independent variables. In effect, one needs a the-ory or model that accounts for the nonrandom assignment of the con-trol variables themselves" (p. 211).

We need a theory of data, not merely in the conventionalepistemological sense, but one that applies to the specificproblem. If comparisons are made, we cannot assume that itis mere chance that some comparative possibilities exist andothers do not. If X varies from one place to another in itslevel, it is just as necessary to ask why it varies as to askwhat its apparent infiuence on Y is. For it is almost certainthat the level of X found in each setting is not due to chance.It is part of the phenomenon under studyevery bit as muchas the apparent dependent variable (p. 229).Following these prescriptions will require a great deal of "soft"work, constructing theories to account for why we see certain combi-nations of various entities and not others, or why some are commonand others are rare, as opposed to the "hard" science work of testingdeductions from such theories. This does not mean tha t we never testhypotheses, only tha t we do a lot more work th an is the cu rrent normbefore proceeding to the confirmatory stage. Paraphrasing Shweder(1986), without the soft side, there is no hard data.The need for "soft" qualitative work to accompany "hard" quan-


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titative work is the result of an important hasic principle: since wemust always view the processes of life from some particular perspec-tive, we must vary that perspective if we are to escape its inherenthiases. Those relationships that persist as we vary our perspectivemore and more are the most certain, the most "rohust" (Wimsatt,1986). "By using a variety of different models, approaches, means ofdetection, or of derivation and comparing the results, we can hope todetect and correct for the biases, special assimiptions, and artifacts ofany one approach" (p. 308).This search for robustness via "triangulation" (Campbell &Fiske, 1959) means that no single academic or professional disciplinecan he counted on to provide adequate understanding of social phe-nomena (Cronhach, 1986). "We can rarely see a topic in proper per-spective if our inquiry employs resources from only one discipline" (p.98). Moreover, even w ithin disciplines, we must have diversity in theperspectives that are hrought to bear on social phenomena. As Fiske(1986) points out, "Each investigator can be viewed as a measuringprocedure, as an instrument for obtaining knowledge" (p. 67). Differ-ences in individual perspectives as a result of differing experiencesand backgrounds are essential in order to remove the hiases resultingfrom relative homogeneity of characteristics of researchers.This is not to say that no standards are to be applied to argu-ments for the importance of different perspectives or interpretations.As noted earlier, relinquishing Absolute Objectivity does not meanembracing total relativism. Or as Cronhach (1986) puts it, "To advo-cate pluralistic tolerance of altern ative accounts is in no way to advo-cate tendermindedness" (p. 104).As Wimsatt (1986) warns, however, we must understand that tri-angulation is itself an heuristic device. It will fail to the extent thatwe do not include sufficient variation in the hiases and assumptionsassociated with our employed perspectives. We must he careful to en-sure t ha t hidden hiases common to multiple approaches do not under-mine the validity of our supposedly rohust observations.

CONCLUSION: NOT A SOCIAL PHYS ICS, BUTRATHER A SOCIAL SCIENCE OF THE POSSIBLEEarlier I discussed the renegotiation of the role of social researchsuggested hy several authors and the fact that social researchers are

often researching questions that are dictated largely hy societal con-


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cem s. An importemt issue he re is th at of consideration of what is "do-ahle" and what is not. Lieberson (1985) addresses this issue in hisintroduction. "Are there questions currently studied that are ha-sically unanswerable even if the investigator had ideal nonexperi-mental data? If so, what are the alternative questions that can bedealt with successfully by empirical social research, and how shouldthey be approached" (p. 8)?I think the answer is obviously th at the re are a g reat many ques-tions of interest which we cannot answer. Identifying the alternativequestions that are answerable and clarifying their relationships toother questions are important steps. This will sometimes lead us tothe point where we are able to answer important but previously un-answerable questions. In other cases it will demonstrate to us thatsome questions, while important, as simply not answerable. As Lie-berson concludes, "we have to develop a better grasp of wh at we w antto explain and what is potentially explicable at a given point ofknowledge . . . What is it that we want to explain? But first, wh at is itth at can be explained?" (p. 235).

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