on the possibility of contextual–quantitative inquiry

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New Ideas in Psychology 24 (2006) 212–228

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On the possibility of contextual–quantitative inquiry

Stephen C. Yanchar�

Department of Instructional Psychology and Technology, Brigham Young University, Provo, UT 84602, USA

Available online 22 November 2006

Abstract

The potential contributions of quantitative methods are rarely discussed in the qualitative research

and theoretical literatures in psychology. However, it is possible that some forms of quantitative

research can fit theoretically within an interpretive framework and provide useful methodological

resources for contextual, interpretive inquiries. Such research, which would examine dynamic modes

of existence and lived experience in context, would extend more flexible and diverse methodological

resources to researchers. This article describes how some types of quantitative research can perform

this function and suggests several caveats regarding their use.

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PsycINFO Classifications: 2260; 2630

Keywords: Methodology; Qualitative research; Quantitative methods; Hermeneutics; Interpretation

1. Introduction

What contribution, if any, can quantitative methods make to contextual, interpretiveinquiry? Although most qualitative researchers would acknowledge that quantitativetechniques and data can, at times and under certain circumstances, assist in the explorationof at least a few research questions, it is conceivable that quantitative research strategiescan offer more than an occasionally useful set of procedures. As I will argue, somequantitative strategies, when carefully interpreted and employed, can make integralcontributions to the meaningful study of human action in context and provide apotentially useful resource for the development of novel questions, theories, arguments,and problem solutions within a contextual framework. More specifically, I will make a case

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ARTICLE IN PRESSS.C. Yanchar / New Ideas in Psychology 24 (2006) 212–228 213

for an alternative approach to quantitative research—termed contextual-quantitative

inquiry—by arguing that there is no convincing reason to reject this possibility out of hand,that some quantitative strategies can provide useful resources for qualitative researchers,and that new forms of quantification can be adapted or developed to support this work.

In presenting this argument, my aim is not to remake or reform various post-enlightenment movements by smuggling the ‘‘quantitative imperative’’ (Michell, 2003, p. 5)into them, having presupposed that these alternative perspectives can only be viable andpersuasive when supported by numeric data. Rather, my aim is to advance the thesis thatno paradigm or movement within psychology should rigidly adhere to a set ofmethodological options determined in advance, and that important contributions cancome from unlikely sources, even from quantitative methods, provided that they are usedcarefully and cohere with contextual, interpretive assumptions. Indeed, from theperspective of several prominent philosophers and historians of science (e.g., Feyerabend,1975/1993; Holton, 1973; Wartofsky, 1980), and in light of the recent proposal for the useof critical methodologies (Yanchar, Gantt, & Clay, 2005), it is inadvisable to pre-establishor routinize certain research methods and practices—qualitative or quantitative—withoutregard for entire ranges of alternative methodological possibilities.

I would also like to note that although I am arguing from a generally hermeneuticperspective that privileges human agency, lived experience, practice, and interpretation incontext (see Gadamer, 1975/1989; Palmer, 1969; Taylor, 1985), contextual–quantitativeinquiry could conceivably be used with a variety of existing qualitative approaches orwithin hitherto unestablished frameworks that break theoretical and methodologicalground. Because contextual–quantitative inquiry can be put to use within a variety ofperspectives, all of which take seriously context and interpretation in one way or another, Iwill use the term contextual, interpretive research to refer to the general realm ofapplication within which contextual–quantitative inquiry is relevant.

2. Neglect of quantitative possibilities in contextual, interpretive research

The contributions of qualitative inquiry, as a general alternative to traditionalquantitative approaches in the human sciences, have been substantial. Perhaps mostnotably, scholars working within the qualitative movement have directed incisive criticismsat traditional social scientific practices and demonstrated the need for a richer view ofhuman existence, which, in turn, has initiated much-needed dialogue (and sometimesheated debate) regarding fundamental issues such as the nature of knowledge, reality,human nature, method, and progress (e.g., Gergen, 1982; Giorgi, 1970; Harre & Secord,1972; Hoshmand, 1989; Manicas & Secord, 1983; Polkinghorne, 1983; Slife & Williams,1995). Such criticism and debate have been accompanied by the advent of a plethora ofqualitative alternatives, the purpose of which has been to offer research strategies thatsuccumb neither to the distorting effects of reductionism, universalism, atomism, andHumean causation, nor the faulty pretenses of scientific objectivity, value neutrality, andmethodological certainty. Furthermore, it is researchers and theorists associated with thequalitative movement who have most strenuously advocated the matching of researchquestions with appropriate methods and the use of flexible, textually-based, andcontextually-sensitive research strategies (e.g., Koch, 1999; Polkinghorne, 1983; Slife &Williams, 1995; Smith, Harre, & Van Langenhove, 1995).

ARTICLE IN PRESSS.C. Yanchar / New Ideas in Psychology 24 (2006) 212–228214

Although the contributions of the qualitative movement have continued in recentyears—as seen in persistent examinations of mainstream social science and in therefinement and ramification of various research strategies—methodologists within thisalternative tradition have typically emphasized innovation along well-accepted qualitativelines rather than the exploration of novel perspectives, methods, and strategies that mayprove useful although they do not carefully follow the methodological pattern ofprominent qualitative approaches. Perhaps not surprisingly, there is little discussion in thisliterature of how quantitative strategies and numeric data may be useful in theunderstanding of lived experience in context (for notable exceptions, see Smith et al.,1995; Westerman, 2004). General neglect of quantitative innovations in this literature haslikely occurred for several reasons, none of which, I will argue, is finally persuasive orsustainable, even though they are all understandable given the historical context in whichthe qualitative movement emerged.

2.1. Total rejection of quantitative research strategies

First, some qualitative researchers may view all forms of quantification in social scienceresearch as fundamentally flawed or inferior, thus rejecting the possibility that even a fewcarefully used quantitative research strategies can contribute to investigations framedwithin a contextual, interpretive framework. To be sure, the traditional quantitativeapproaches of mainstream psychology reflected problematic assumptions and practices, asmany critics have pointed out (e.g., Danziger, 1990; Hornstein, 1988; Koch, 1999;Polkinghorne, 1983; Slife & Hunsaker, 2001; Slife & Williams, 1995). Although criticismsof quantification in psychology have typically been aimed at methodological staples suchas operationism, data aggregation, inferential statistics, theory neutrality, prediction,control, and various forms of scaling and measurement (e.g., Bakan, 1966; Danziger, 1985,1990; Hornstein, 1988; Lamiell, 1995; Meehl, 1978; Michell, 1997; Robinson, 2000; Rucci& Tweney, 1980; Slife & Hunsaker, 2001; Spackman & Williams, 2001), it is a relativelyeasy conceptual step to the more extreme view that any conceivable uses of numbers,magnitude, and other forms of quantification will necessarily lead to faulty or irrelevantresearch and thus are to be rejected. Although it is unlikely that this anti-quantitativeposition would be explicitly endorsed by many qualitative researchers, the practical impactof something like it is manifest in the literature, which, as stated above, evidences a lack ofdiscussion regarding the potential contributions that quantitative research strategies canmake to contextual, interpretive research.A strictly qualitative research focus, at least for some in the discipline, is likely animated

by the belief that there are two basic kinds of research methods from which to choose andtwo superordinate ‘‘paradigms’’ from which those methods derive—qualitative andquantitative. Because the basic views of reality and knowledge that traditionally underpinthese two general types of research are theoretically incompatible (e.g., Guba & Lincoln,1988; Marecek, 2003; McGrath & Johnson, 2003; Rogers, 2000; Skrtic, 1990; Smith &Heshusius, 1986; Yanchar, 1997), there appears to be no other option than to embrace oneparadigm or the other and make use of the methodological resources it offers. From thisperspective, talk of numbers, magnitude, and measurement commits one to the assumedquantitative paradigm, and talk of interpretive meanings in context commits one to theassumed qualitative paradigm. A third position involving various mixed-method andmixed-model designs (Hanson, Creswell, Clark, Petska, & Creswell, 2005; Tashakkori &


Teddlie, 2003) may appear to enable a move beyond the qualitative–quantitative debate,but, for reasons described below, cannot ameliorate what others have termed the‘‘paradigm wars’’ (Gage, 1989, p. 4; Hoshmand & Martin, 1994, p. 172) of the past severaldecades.

While the rudimentary distinction between qualitative and quantitative paradigms mayhave been helpful in some ways, and while it is clear that all methods will inevitably beinformed by theoretical assumptions, it is not the case that there are only two basicperspectives from which to draw theoretical and methodological resources and it is not thecase that only two monolithic types of methods are conceivable (see also Hammersley,1996). Indeed, numerous philosophical frameworks, such as unique forms of positivism,neopositivism, critical realism, pragmatism, post-structuralism, neo-classicism, hermeneu-tics, phenomenology, constructivism, feminism, critical theory, and others offer theoreticalspace for the development of a variety of methodological approaches. While it is clear thatnot all of these frameworks will be equally appealing to researchers with qualitativeleanings, it is also clear that there are diverse (though possibly related and overlapping)perspectives by which post-enlightenment research and theory may be framed. Perhapsmore importantly, however, there is no necessary reason why researchers must situatethemselves squarely within any of these overarching positions and conform to prevailingmethodological norms. As was recently argued (Yanchar et al., 2005), the most promisingresearch programs will not be paradigmatically orthodox, but contextual and evolvingtheories of inquiry that involve well-thought-out, indigenous assumptions about thesubject matter to be investigated and fallible research strategies—adopted, modified, orinnovated—that cohere with those assumptions and provide the most promising resourcesfor fruitful inquiry. From this perspective, a focus on theory construction, innovativemethod use, critical analysis, and problem solving are to be privileged over settledtheoretical perspectives and formulaic methods.

Regarding the potential utility of quantification per se, it can be seen that thequantitative imperative of traditional psychological science is only one of many possibleconceptions of numbers and their uses. When viewed from other cultural, historical, orphilosophical perspectives, numbers can be seen to take on different meanings altogether(Slife & Hunsaker, 2001). Thus, demonstrations of the theoretical and practical failings ofone quantitative approach do not, ipso facto, imply failings of all possible quantitativeapproaches. Put simply, the problem is not numbers per se, but the appropriation ofnumbers into a framework that cannot do justice to the meaning and possibilities ofhuman life. From this perspective, there is no a priori reason why researchers interested incontextual, interpretive understandings must reject all forms of quantitative data andnumeric interpretation. Indeed, from this perspective, it is possible that some quantitativeresearch strategies—either newly innovated or reconstrued—may be compatible with, andgreatly expand, the methodological resources available for contextual, interpretiveresearch. Contextual–quantitative research strategies may thus reveal human experiencein new and illuminating ways without reintroducing the problems of traditional,quantitative research in psychology.

2.2. Use of quantitative strategies through mixed-methods

A second possible reason why little discussion and innovation of quantitative procedureshas occurred in the qualitative literature concerns the advent of mixed-methods


approaches that encourage the eclectic use of whatever method or methods seem tobest address particular research questions in context (e.g., Tashakkori & Teddlie, 2003).If traditional quantitative and qualitative methods can be jointly and strategically usedwithout contradiction, then there is little reason to be concerned about fundamentalphilosophical issues and little reason to innovate more serviceable quantitativealternatives.Although the tailoring of methods to questions and use of triangulation are surely

improvements over traditional methodological monism, calls for mixed-method ap-proaches within psychology (e.g., Hanson et al., 2005; Hoshmand & Polkinghorne, 1992;Howard, 1986; Todd, Nerlich, McKeown, & Clarke, 2004) have been vague on howresearch practice and methods can successfully become more inclusive, innovative, andpluralistic. For instance, how does one identify the most appropriate method or methodsfor particular research questions? When are certain methods most appropriate and why?What is the role of methodological innovation in mixed-method research? Cantheoretically incompatible methods be usefully and coherently mixed within a single studyor a program of research? If so, why and how? What kinds of criteria should be used toevaluate the quality of mixed-method or cross-paradigm studies?Such questions are not trivial. Granted that there is no objective standpoint from which

they may be answered, human judgment must play a prominent role in the process ofdeliberation, and such judgment, of course, involves assumptions and values that must becritically examined (Yanchar & Williams, in press). Moreover, if—as many have argued(e.g., Burtt, 1954; Danziger, 1985; Gadamer, 1975/1989; Slife & Williams, 1995; Yanchar,1997)—research methods are informed by a network of presuppositions and yield theory-based, value-laden results, then researchers employing theoretically incompatible methodswill either yield incompatible and incoherent results or invoke a default subsumptionwherein the meaning of one method and its data are absorbed into another. Criticalanalyses have suggested that the latter is often the case in mainstream research, withqualitative data being appropriated into a traditionally quantitative framework (e.g.,Bryman, 1984; Marecek, 2003; McGrath & Johnson, 2003; Ponterotto, 2005; Smith &Heshusius, 1986; Yanchar & Williams, in press). A related issue has to do with generalstandards for quality and rigor in a pluralistic science, namely, that if such standards arebiased against entire ranges of methodological possibilities (e.g., qualitative orquantitative), or against the very idea of methodological openness and innovation, thenthe likelihood of scientific progress is greatly diminished (Feyerabend, 1975/1993;Hammersley, 1996; Yanchar et al., 2005). Problems such as these are not insuperable,but they have not been adequately addressed in the literature to this point.

2.3. Preoccupation with other tasks

Third, it is possible that quantitative research possibilities have been largely neglected inthe qualitative tradition because qualitative theorists have been preoccupied withimportant tasks such as critiquing the traditional view of science and quantification,defending their own philosophical positions, and developing alternative research strategies.Historically speaking, attention paid to these concerns may have come at the expense ofexpanding methodological possibilities to include appropriate quantitative procedures.Indeed, given the emphasis on countering the traditional research hegemony of the socialsciences and on the paradigm wars that followed, it is not entirely surprising to see little


discussion of vexing issues that arise in the combined use of widely divergent methods andlittle emphasis placed on the innovation of quantitative or other types of research strategiesnot typically seen in the qualitative literature. As understandable as this lack of innovationand inclusion may be, however, it ultimately leads to an unhelpful methodologicalposition. Because any method will bring with it strengths and weaknesses that may not bewell-suited to a researcher’s assumptions and purposes, it is inadvisable to proscribecertain research strategies and forms of inquiry—qualitative or quantitative—on the basisof paradigmatic or philosophical fiat.

Of course, arguments in favor of methodological flexibility, openness, and innovationare unlikely to spark controversy among at least some qualitative theorists and researcherswho have recognized the dangers of a qualitative orthodoxy (e.g., Hammersley, 1996;Yanchar et al., 2005) or who have called for methodological openness, the tailoring ofmethods to questions, and various forms of triangulation (e.g., Greene, Caracelli, &Graham, 1989; Polkinghorne, 1983; Tashakkori & Teddlie, 2003; Wertz, 1999).Nonetheless, there has been little focused discussion about such concerns withinpsychology and few attempts to work out complex and often subtle issues that arise inthe innovation, and combined use, of diverse research strategies.

3. The possibility of contextual–quantitative inquiry

The uncritical acceptance of quantitative procedures by many in the discipline’smainstream has obscured the need to address important theoretical questions, not the leastof which concerned the very idea that psychological phenomena could be meaningfullyexamined and understood using standard quantitative strategies (Hornstein, 1988).Although it is often taken for granted in the mainstream that psychological phenomenacan be meaningfully studied in this way, many observers have argued that they cannot.Danziger (1985, 1990), for instance, demonstrated that mainstream researchers typicallyview the numeric ordering of data (e.g., observations of behaviors, questionnaireresponses, and so on) as the reality of the phenomena being studied, giving rise totheoretical models that reflect the logical structuring of those data and quantitativetechniques. Notwithstanding the ubiquity of this practice, such quantitative data oftenoffer little insight into the lived experiences and meanings of human beings in context. Abit more pointedly, Danziger (1990) persuasively argued that abstract numbering schemes,the serializing of behavior, and commonly employed forms of data aggregation oftentransform meaningful human experience and action into segmented, decontextualizedinstances of natural laws, the apparent success of which has prompted an unfortunate shift‘‘from quantification to methodolatry’’ (p. 136). Other critics have similarly sensed theinappropriateness of traditional forms of quantification in psychology, arguing that theysuffer from a lack of sensitivity to the richness and diversity of meaningful humanexperience (e.g., Giorgi, 1970; Hoshmand, 1989; Howard, 1986; Morrow, 2005;Polkinghorne, 1983; Slife & Gantt, 1999), and that, ontologically speaking, human mentallife is not compatible with the quantitative forms of inquiry often imposed upon it(Hornstein, 1988; Michell, 1997).

In light of such criticisms, traditional quantitative techniques hardly appear tooffer useful resources for contextual, interpretive research. Indeed, such criticismsprovide an ominous warning to any theorist calling for the use of quantification inpsychology—that, at a minimum, such uses must be carefully formulated and employed


in order to be compatible with research that moves beyond the quantitative im-perative. Although incorporating quantitative methods into contextual, interpretiveresearch may be theoretically and practically challenging, it is not outside the realmof possibility and, as mentioned above, has the potential to offer a variety of helpfulresearch strategies. The case for contextual–quantitative research can be strengthened,however, by considering three related points regarding the very possibility of meaningfulquantification in psychology and the methodological resources that would help bring itabout.

3.1. Meaningful quantitative interpretation in context

First, it is possible that some aspects of human action and experience can bemeaningfully interpreted in terms of magnitude or frequency, the relevance of which bearsdirectly on the social, moral, practical, and spiritual fabric of people’s lives. It may be thecase, for instance, that at least some aspects of decision making, problem solving,creativity, learning, and related activities are meaningfully and contextually experienced interms of degree of difficulty or ease, relevance or irrelevance, goodness or badness, like ordislike, and so on. To state that human action and experience exist this way, of course, is tostake out an ontological position of high relevance. Although there is reason to believe thatnot all aspects of human mental life and action exist as quantifiable phenomena, there isalso reason to believe that humans are capable of understanding at least some lifeexperiences and activities in terms of magnitude or frequency without falling prey toprofound distortion (see, for example, chapters in Smith et al., 1995). Moreover, lifechanges taking place over time or life events experienced as parts of a larger process mightalso be fruitfully examined via appropriate quantitative procedures in conjunction withother qualitative approaches. Whereas the transformation required to generate scaled datamight not be viable in some or many such cases, some ordinal-based forms of measurementmight be used to generate numeric patterns that are more or less faithful to the experiencesand activities studied and the contextual, interpretive assumptions underlying the research.Indeed, some have argued that most psychological data are best interpreted as ordinal-based in any event (e.g., Laming, 1997). Whether or not scaled data are found to be usefulfor contextual–quantitative inquiry will depend on how those data are conceptualized andapplied.

3.2. Development of appropriate quantitative research strategies

Second, it is possible that new quantitative research strategies could be developed tocohere with contextual, interpretive assumptions and provide additional methodologicalresources for the investigation of complex, dynamic human events and experiences. Forexample, such quantitative strategies could be helpful in providing a new perspectivefrom which to look at some experiences typically studied qualitatively, in providinga broader methodological context for interpreting life experiences, or in helping todescribe and understand meaningful changes that occur based on contextual circumstances(in a type of modified repeated-measures format). It is also possible that newly deve-loped quantitative strategies could make use of frequency data that provide addi-tional insight into important life experiences. This could occur, for instance, whenstudying phenomena such as the number of episodes of a certain type occurring at


various ages in a person’s life, the number of times a student tries before giving upon a task, or how often people in a study of spiritual experience pray, attend organizedreligious services, or feel communion with a higher power. Other applications that cannotbe predicted in advance are surely possible as well. Such contextual–quantitativeapproaches would not replace more traditional qualitative research and its evolvingforms of inquiry, but it is conceivable that a richer perspective could be brought to someresearch questions by virtue of novel research strategies that quantify without distortingcontextual meanings.

3.3. Reformulation of existing quantitative research strategies

Third, it is possible that some existing strategies could be useful, provided that they canbe interpreted, or reinterpreted, to fit within a contextual, interpretive framework. AsDanziger (1985) pointed out, such a possibility seems to have largely escaped traditionalresearchers—indeed, it may have also escaped many qualitative researchers—even thoughit is conceptually possible. Educational researchers Shaffer and Serlin (2004) took a step inthis direction by formulating the ‘‘intra-sample statistical analysis’’ (p. 14), a statisticaltechnique that assists in drawing warranted conclusions about patterns of activity inqualitative studies such as grounded theory without aggregating data across participants,generalizing to populations, or relying on formulaic output such as p-values or indices ofcovariation. Such analyses can help explore and support claims about individualexperiences in a variety of settings (e.g., educational, clinical) without recourse to thevalues, assumptions, and objectives of traditional quantitative research. Whether or notthis particular technical contribution will be persuasive to qualitative researchers inpsychology, and whether or not techniques such as these will be used widely in the socialsciences, are open questions. Nonetheless, this example demonstrates a willingnesson the part of some researchers to move beyond old dichotomies and suggests thatcarefully reinterpreted quantitative techniques need not be destructively transformativeor reductive.

Though not particularly common, other relevant cases of quantitative data informingcontextual, interpretive inquiry can be seen in investigations based on Q-methodology(e.g., Stainton Rogers, 1995), the use of repertory grids (Smith, 1995), studies of mentalimagery (e.g., Ahsen, 1985, 1990), and personality research (e.g., Gergen, Hepburn, &Comer Fisher, 1986; Lamiell, 1995). By carefully interpreting and applying existingresearch tools and novel data analysis techniques that avoid problematic forms of dataaggregation, these researchers have, in different ways, provided meaningful and evocativequantitative results. That these alternative approaches fit coherently into a contextualperspective illustrates two related points: that numeric procedures can be used innovativelyto clarify and understand central aspects of human experience, and that the innovative useof numbers does not necessarily vitiate a commitment to contextual, interpretive researchpractices.

The utility of such quantitative approaches likely stems from the fact that qualitativeand quantitative approaches share at least a few conceptual and practical commonalities.As Hammersley (1996) pointed out, both forms of inquiry, broadly construed, involve datathat is at least one-step removed from actual lived experience (as an abstraction orreflection), both can involve verbal and textual meanings as well as judgments ofmagnitude and frequency, both can involve meanings that range from vague to precise,


and both can be performed in artificial or natural settings (see also Bryman, 1984; Yancharet al., 2005). Thus, Hammersley concluded:

There is no stark contrast to be found, then, between verbal and numeric data, oreven between precise and imprecise, structured and unstructured, and contextualizedand uncontextualized data. Rather, there is a range from more to less precise, moreto less structured, and more to less contextualized types of data from which tochoose. Furthermore, our decisions about what levels of precision, structure, andcontext are appropriate in relation to any particular study should depend upon thenature of what we are trying to describe, upon the likely accuracy of our descriptions,upon our purposes, and upon the resources available to us, not on ideologicalcommitment to one methodological paradigm or another (1996, p. 162).

4. Toward a reconceptualization of quantification

However, the similarities between qualitative and quantitative research strategies areonly partial, and, as suggested above, many, if not most, extant quantitative strategiesreflect modernist values and assumptions that are not compatible with a contextual,interpretive framework; indeed, as suggested above, such strategies are likely to distortrather than reveal important dimensions of human experience. What is required, then, isnot an eclectic combination of methods—having taken for granted the fundamentalcompatibility of qualitative and quantitative methods—but a well-thought-out, theory-driven approach that is harmonious with the interpretive thrust of many researchersworking outside of psychology’s mainstream. As Danziger warned:

In order to establish the relevance of the results obtained for the theory being testedone ought to be able to show that the structure which one’s numeric system hasimposed on the data is at least broadly congruent with the structure suggested by thetheory. If it turns out that the numerical structure and the theoretical structureinvolve different assumptions, then the theory one is testing is not the theory onewanted to test but at best some vague analogue thereof. (1985, p. 4).

From this perspective, there can be a justifiable basis for considering both qualitativeand quantitative possibilities in the practical conduct of research, provided that atheoretical reconstrual of extant methods can satisfactorily render them compatible withthe interpretive theories and phenomena to be investigated.How should researchers go about developing an alternative view of quantification that

can inform the development of novel research strategies and the reconstrual of existingapproaches? It is possible that the adoption of at least some assumptions, concepts, andactivities prevalent within the qualitative tradition may be applied to contextual–quanti-tative research, thus eliminating the need for a wholly new theoretical framework. In part,this is a reasonable tack, although some discussion of how to replace traditionalquantitative concepts and activities—such as commonly accepted forms of measurementand validity—will also be required since they have become conflated with the very idea ofquantification. Due to the complexity of this task, I can provide only a brief overview ofhow contextual–quantitative inquiry can be conceptualized and evaluated, emphasizingthe theoretical shift (a) from self-contained variables to dynamic modes, (b) from


measurement to interpretation in context, (c) from internal validity to trustworthiness, and(d) from generalizability to transferability.

4.1. From self-contained variables to dynamic modes

In traditional quantitative theorizing and research, the contextual human being isinvolved only tangentially; the actual focus of investigation is some narrower topic ofinterest, typically interpreted as a natural, determined process that can be decomposed intoontologically self-contained phenomena—that is, variables. Variables, under the tradi-tional experimental conception, are manipulated (independent variables) and measured(dependent variables) in order to arrive at some causal relationship among them. In thisconception, independent variables precede dependent variables along the hypothesized lineof time, creating the effect (or lack of effect) that researchers will observe and report (Slife,1993). Given this view of science—based on reductionistic, atomistic, and deterministicassumptions—the use of variables is taken for granted.

If the subject matter of psychology is viewed differently, however, then the idea of avariable may change with it. If, for instance, human experience and action are viewed asmeaningful, volitional, and contextual, then it would be most appropriate not to conceiveof research as the study of self-contained (e.g., ‘‘independent’’) variables. Otherconceptions and terminology would be more plausible and useful, such as modes, actions,or experiences, that are not causally related in Humean fashion, but are meaningfully andcontextually related as co-constituting parts of a broader context, lending one anothermeaning and identity. From this viewpoint, ‘‘variables’’ (i.e., modes, characteristics,actions) are contextually related rather than linearly related, taking on a simultaneousformal–causal relationship (Rychlak, 1988), and the purpose of quantification is to clarifythese co-constituting parts and thematize them into dynamic, contextual patterns.Considered together, thematized (quantified) parts can form coherent accounts ofmeaningful human experiences. Other contextually related phenomena—quantified andstudied in various ways—could also be viewed as parts of meaningful experiences incontext.

4.2. From measurement to interpretation in context

To be sure, measurement is a central part of traditional quantitative research; withoutmeasurement of some form or another there would be very little quantitative data (at leastof the traditional type). More recently, the field of measurement has undergone impor-tant conceptual and technical changes, including the advent of Rasch scaling, multi-dimensional scaling, item response theory, structural equation modeling, and latentvariable growth modeling. These innovations have greatly expanded the capabilities andsophistication of researchers whose investigations require psychometric identification andassessment of so-called ‘‘latent’’ variables. Notwithstanding these important methodolo-gical advances, however, the basic project of uncovering or identifying isolable variables byvirtue of tests and questionnaires so they may be viewed in relation to other variables hasnot diminished in importance. It is assumed, often implicitly, that this identificationprovides a glimpse into some underlying aspect of the human experience—some set ofindividual difference factors—that are consistent across situations and time and that canbe used to better predict other mental processes and behavior. Measurement, thus


conceived, tends to distort human experience by reducing it to a collection of static,self-contained variables that can be systematically quantified via psychometric instrumentsand correlated.Measurement conceived alternatively, however, holds greater promise in thematizing

various aspects of human experience in context without presuming to isolate anddecontextualize variables. From this alternative perspective, measurement can be viewed asa process whereby people are offered a language for self-interpretation and self-expressionin context. Thus, scores on a test or questionnaire would be viewed as contextual self-interpretations subject to fluctuation based on the changing nature of the context andthe test taker’s involvement in it. A person’s score would be, in this sense, an interpretiveaccount of his or her action and experience at a given time rather than an invariantindex of a static ability. Importantly, data from such forms of measurement neednot be aggregated in damaging ways. As some have shown, data from individuals can beusefully and systematically analyzed without losing information about the individualexperience in context (e.g., Ahsen, 1985; Shaffer & Serlin, 2004; Smith, et al., 1995). Thus,bearing in mind the dynamic nature of human experience, carefully designed andimplemented tests can help create meaningful contexts and experiences, thematize certainexperiences in a given situation, and, in all likelihood, be useful in ways not yetconceptualized.The contextual, interpretive approach to measurement I present here could hardly be

acceptable from a more traditional standpoint. How could a test be reliable when thescores it generates for a single person fluctuate according to context? Bearing in mind a fewnotable exceptions—such as ‘‘state’’ anxiety—such scales would be considered flawed, ormore specifically, unreliable. Contextual–quantitative research, on the other hand, ispredicated on the ontological assumptions that human experience and action aresituationally responsive and volitional; thus, the idea of test reliability, as traditionallydefined, is a suspect concept and hardly relevant to the type of quantitative inquiryadvanced here.At the same time, traditional test validity concerns such as construct validity and content

validity may still be of some relevance, provided that (a) they are construed in a way thatcoheres with the assumptions of contextual, interpretive research; (b) that these conceptsare viewed as parts of a larger argument or interpretation (based at least partly on testdata) rather than transcendent properties of a test; and (c) that it is understood thatcontextual interpretation might be unreliable according to traditional standards yet stillable to communicate something meaningful about lived experience, such as when aperson’s action or ability fluctuates from one situation to another. Additional theoreticaland practical issues surrounding the use of measurement and test validity in contextual,interpretive research would have to be worked out as quantitative research strategies andtests are modified or developed.

4.3. From internal validity to trustworthiness

Internal validity, a crucial feature of traditional quantitative research, rests on a set ofassumptions (e.g., atomism, Humean causation, linear time, and objectivity) that render itincompatible with most contextual, interpretive research. The rejection of traditional‘‘internal validity’’ criteria, however, is not particularly problematic, because qualitativelyoriented researchers have suggested many alternative conceptualizations concerned with


the trustworthiness of studies and results. However, trustworthiness is itself a complex,unsettled, and sometimes controversial topic in the qualitative literature (Lincoln & Guba,2000; Merrick, 1999; Morrow, 2005). This state of affairs likely results from the centralrelevance of this issue, which Lincoln and Guba (2000, p. 178) demonstrated by boiling itdown to two practical questions:

Are these findings sufficiently authentic (isomorphic to some reality, trustworthy,related to the way others construct their social worlds) that I may trust myself inacting on their implications? More to the point, would I feel sufficiently secure aboutthese findings to construct social policy or legislation based on them?

From this perspective, some concern about the trustworthiness of data is inescapable.The crucial task, of course, is for contextual, interpretive researchers—including thoseconducting qualitative research and/or contextual–quantitative inquiry—to formulatepersuasive arguments that take into consideration their own theoretical commitments aswell as those of the audiences to which the arguments will be presented.

Because qualitative researchers with different perspectives have approached the issue oftrustworthiness differently, multiple approaches are available (Morrow, 2005). Guba andLincoln (e.g., Guba, 1981; Lincoln, 1990; Lincoln & Guba, 1985), who proposed ‘‘parallel’’criteria (Guba, 1981, p. 76) such as credibility and confirmability, did much to initiate andcatalyze the original discussion of trustworthiness in the qualitative domain. Although thisinitial approach to trustworthiness—as a response to traditional notions of validity,reliability, and objectivity—may seem somewhat reactive at the present time, it nonethelessprovided a useful frame of reference for researchers and demonstrated that contextual,interpretive research in general could be subjected to standards of reasonableness and rigornot identical to those of the dominant quantitative tradition (Morrow, 2005). Moreover,the evolution of their thought regarding trustworthiness has continued to offer promisingways of interpreting and evaluating qualitative results (e.g., Lincoln, 1995; Lincoln &Guba, 2000). Other theorists have also proffered understandings of quality ortrustworthiness that can be generally applicable (Erickson, 1986; Eisenhart & Howe,1992; Marshall, 1990; Merrick, 1999; Stiles, 1993), or that are indigenous to particularforms of qualitative inquiry, such as phenomenology (e.g., Giorgi, 1988), grounded theory(Gasson, 2004), and narrative interviewing (Kvale, 1996).

Although the parallel criteria for trustworthiness formulated by Guba and Lincolnmight provide the most useful starting point for evaluating contextual–quantitative inquiryat this juncture, other proposals, such as that of Stiles (1993), which emphasized theinterplay of existing understandings and new insights, the perspectives of those affected bythe research, and the asking of ‘‘what’’ rather than ‘‘why’’ questions, would also seemapplicable. Moreover, because contextual–quantitative research strategies could beconducted within the purview of other contextual, interpretive approaches, the task ofjudging contextual–quantitative inquiry could involve some of the same considerations asit does for qualitative forms of inquiry, provided that these considerations are adapted toaccommodate quantitative research strategies where necessary. In any event, moreimportant than developing or adopting a standard set of criteria for trustworthiness isrecognizing that ‘‘validity’’ issues can be addressed in ways that allow for the criticalexamination and evaluation of the products of contextual–quantitative research.


4.4. From generalizability to transferability

The assumption of universalism—that true results should be raised to the level ofuniversal statements or at least be applicable to entire populations—has deeply influencedquantitative research, as evidenced by the longstanding pursuit of general laws of behaviorand the near-ubiquitous use of inferential statistics (Danziger, 1985, 1990; Hornstein, 1988;Slife & Williams, 1995; Teigen, 2002; Thompson, 1996). Indeed, objections to researchwith small sample sizes almost inevitably entail the concern that findings will not generalizefrom the sample in question to a broader population. From this traditional perspective,research findings that do not generalize in this way are largely pointless.On the other hand, if researchers begin with the ontological assumption that human

experience is contextual and interpretive and use research strategies that fit within thisperspective, then quantitative results will be viewed as theory-laden understandings ofhuman phenomena in context. Such understandings would not be expected to supportinferences about broader populations or give rise to lawful generalizations. Rather, theywould be used to thematize something interesting and meaningful about instances ofhuman experience and action that can illuminate understanding of similar experiences andactivities in other contexts. Lincoln and Guba (1985, p. 297; see also Guba, 1981) havereferred to this function as ‘‘transferability’’—a process whereby those who wish to applyor extend a set of research findings transfer them, so to speak, by exploring theirimplications for related experiences or contexts. According to this notion of transferability,contextual results might usefully apply to, or yield insight about, similar contexts orprovide interesting insights about other (less similar) settings. Unlike the traditional viewof generalization, however, the process of transfer is conducted by those who seek to applythe understanding in a new situation rather than those who conducted the original study.As Lincoln and Guba (1985, p. 316) stated: ‘‘it is not the [original researcher’s] task toprovide an index of transferability; it is his or her responsibility to provide the data base

that makes transferability judgments possible on the part of potential appliers’’ (italics inthe original). Of course, richer data are more likely to support more substantial andilluminating transfer.

5. Beyond ‘‘qualitative’’ inquiry?

Contextual–quantitative inquiry, framed in this manner, might be viewed as part ofwhat is commonly known as qualitative inquiry. It is debatable, however, whether thephrases qualitative research and qualitative methods are optimal descriptors of the range ofmethodological possibilities available for contextual, interpretive research. If researcherspursue data-based interpretations of meaningful human action and experience in context,and if some quantitative approaches can be useful and harmonious partners in thisendeavor, then it may be time to move from the traditional qualitative-quantitativeterminology and its tensions to new and possibly more productive horizons (see alsoErickson, 1986). Of primary importance would be a shift away from method-centeredscholarship and methodological eclecticism, toward a form of scientific practice thatemphasizes the creative formulation of theories and the solving (perhaps tentatively) ofpractical and theoretical problems. Appropriate research strategies—involving assump-tions about the target subject matter and explicitly-theoretical, compatible, evolvingresearch strategies—can facilitate this work (Yanchar et al., 2005). More specifically,


quantitative strategies that are compatible with the commitments of contextual–interpre-tive research can extend the methodological resources available to contextual, interpretiveresearchers in a variety of ways and facilitate the tasks of theory construction and problemsolving.

Clearly, contextual–quantitative inquiry could be misused or misappropriated in waysthat reintroduce the quantitative imperative and that fail to realize the potentials I haveadumbrated here. It is safest to assume that no method of inquiry is perfect and thatcritical examination of methods-in-use is always required of researchers. This caveat,however, condemns contextual–quantitative inquiry no more than it condemns any othermethod of investigation. Indeed, just as an incautious or erroneous use of numbers andquantification can lead to theoretical or scientific dead-ends, so can incautious orerroneous use of words and text. As Michell (2003) pointed out, there was nothing aboutthe doctrine of positivism that demanded quantification; in fact, much of logical positivismwas based on the reduction of natural language and lived experience to an axiomatic-logical linguistic structure thought to provide metaphysically-neutral descriptions—that is,a sense-data language in which equivocation would be eradicated. More generally,theorists have noted that all languages are, in some sense, restrictive; they reveal andthematize in certain ways while concealing and obscuring to a lesser or greater extent (e.g.,Dreyfus, 1992; Slife & Williams, 1995). This point applies to textual forms of interpretationas well as numeric ones and implies that it is mistaken to attribute to all forms ofquantification the theoretical drawbacks of positivism and its historical manifestations inthe social sciences.

Finally, I would like to comment briefly on the theoretical work required in theformation of contextual–quantitative research strategies. Such work can involve thedevelopment of measurement schemes that are less likely to decontextualize and distortexperience than traditional approaches, research designs that are sensitive to experiences ofmeaning and change in context, and new theories and techniques for the analysis ofcontextually sensitive numeric data (see also Lamiell, 1995). In all cases, the principalobjective would be to foster creative ways of engaging participants and the data theyprovide so that important experiences are more likely to become apparent and understood.Workers in this arena face clear challenges, such as developing these new forms ofquantitative reasoning while being familiar with the substantial body of thought within thequalitative tradition and with the methods and techniques it has produced. Such work willlikely require unique uses of numbers and text that have not heretofore been available orwidely disseminated and utilized. However, such innovations need not be viewed asfundamental alterations of the nature and purpose of contextual, interpretive research.Rather, they can be viewed as useful extensions of the important theoretical andmethodological developments already taking place outside of the discipline’s mainstream.Such developments, which have the potential to take psychology beyond thequalitative–quantitative debate, can involve numeric data while recognizing thatmainstream psychology ‘‘does not own quantitative methods’’ (Lamiell, 1995, p. 160).

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