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The Role of Theory in Scholarly Fields

Scholarly Fields

Fundamental Purpose

The primary purpose of any scholarly field is to generate knowledge about the field’s focal phenomenon, then to communicate that knowledge. In order to understand this purpose statement, we need to clarify the meaning of knowledge and focal phenomenon.

In any scholarly field, knowledge is not simply a finding from one study nor is it a listing of findings from multiple studies. Instead, knowledge is a structured, detailed description about what is believed to be known about a field’s focal phe- nomenon. While the building blocks of knowledge are the findings from individ- ual studies, those building blocks by themselves are not knowledge; they need to be evaluated for validity and usefulness, then assembled into a meaningful struc- ture in order to attain the status of knowledge. The evaluation involves scholars assessing the validity of findings so they can discard the claims that are found to be faulty. Then the valid findings need to be calibrated for importance so that the most important findings can be used to form a solid core when assembling those findings into a system of explanation.

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A field’s focal phenomenon is the entity that scholars in that field are trying to understand and explain. For example, the focal phenomenon of the field of chem- istry is physical matter that is studied by examining atoms and molecules. The focal phenomenon of the field of biology is living things that are subdivided into botany (the study of plants) and zoology (the study of animals). The fields regarded as social sciences are concerned with human thinking and behavior. Within the broader field of the social sciences, the scholarly field of psychology is focused on the focal phenomenon of the human mind; the field of sociology focuses on human interactions in groups; the field of economics focuses on the exchange of resources; and the field of media effects focuses on how the media exert an influ- ence on individuals and aggregates.

Development of Scholarly Fields

Scholarly fields are generated when scholars become attracted to a phenomenon and are driven by curiosity to learn all they can about that phenomenon. As more scholars are attracted to studying a phenomenon and as they begin speculating about the nature of that phenomenon, they form a community to share ideas in articles, books, conference papers, and websites.

The speculation about the focal phenomenon reveals scholars’ ontological beliefs, which are beliefs about the nature of the phenomenon, such as its size, its components, its processes, and how it interacts with other phenomena in the social and physical worlds. Researchers begin testing those speculations to find out which are most useful. These tests reveal researchers’ epistemological positions, which are beliefs about the ways in which humans can come to know the phe- nomenon and the limits of that knowing. Because scholarship is a community endeavor, researchers publish their findings in scholarly outlets so their ideas about the phenomenon as well as their research findings can be shared with other schol- ars in the field.

Scholarly fields begin in an exploratory mode, where assumptions dominate. There are many assumptions that must be made early in the history of a scholarly field in order to answer questions such as:  What are the most important con- cepts that can be used to explain the phenomenon? How should those concepts be defined? How can those concepts best be measured in research studies? How are those concepts related to one another? When a field is new, these questions have no existing answers or the answers are not very useful, so researchers must specu- late about possible answers. Those speculations are evaluated by other scholars so that the faulty speculations can be weeded out.

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The development of knowledge in a field always involves a hermeneutic process. This means that scholars try to leverage the result of an individual research study to argue that the result indicates a general pattern; scholars then use that speculated general pattern to explain an individual result. When a field is well developed, it is relatively easy to use this hermeneutic process because scholars have a well-articulated big picture of their phenomenon that allows them to easily understand any individual research finding. However, when a field is new, the big picture is fuzzy, so scholars rely on speculations based on what they think are reasonable assumptions at the time. It is rather like trying to solve a huge puzzle with thousands of pieces without knowing what the picture of the puzzle will reveal when all the pieces are assembled. Scholars must make reasonable guesses about what the picture is in order to start placing pieces in what they hope will be useful positions so that all the pieces go together in a way to reveal a coherent big picture. That is, scholars use their assumptions about what the big picture of the phenomenon might be in order to design their research studies. If their assumptions about the phenomenon are faulty, then the design of their research studies will produce findings of questionable value, that is, those results will be diffi- cult to interpret or those results will not seem to make sense.

The hermeneutic process follows a circular procedure of using assumptions to support other assumptions. In many fields, scholars will attempt to break open this circular process of pure reasoning by introducing empirical tests that can be used to generate tests of those assumptions. Over time, those assumptions that have been found to generate support evolve into trusted empirically based findings, while those assumptions that fail to generate sufficient support from a program of empirical tests are regarded as faulty and are replaced with alternative assumptions.

The typical growth pattern in scholarly fields is by gradual evolution of ideas as scholars debate speculations and test them for empirical support. Gradually over time, scholars coalesce around certain ideas as being better descriptors of the field’s focal phenomenon. These ideas become institutionalized as the accepted knowledge about the focal phenomenon. Scholars take these foundational ideas for granted as they try to build knowledge beyond this core.

In contrast to evolution as a growth pattern, some fields experience a revolution where scholars grow tired of accepting the foundational core ideas and challenge them as being outdated, too limiting, or faulty in some way (Kuhn, 1970). Growth through revolution occurs suddenly after a period where thinking is stuck, and the growth of knowledge slows down and might even stop. Scholars keep doing the same kind of scholarship over and over until the marginal utility of each new study approaches zero. Then a creative scholar introduces a new way of thinking about the phenomenon typically by strongly challenging an assumption then altering it

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in a way that suggests a fresh way to build understanding about the field’s focal phenomenon. If that fresh thinking attracts enough scholars and if the new schol- arship does indeed result in new insights about the phenomenon, then the revo- lution is successful and alters the direction of how scholars explain the field’s focal phenomenon.

Theories

What Is a Theory?

The word “theory” has many different meanings in everyday language. Reynolds (1971) says that it can refer to “(1) vague conceptualizations or descriptions of events or things, (2)  prescriptions about what are desirable social behaviors or arrangements, or (3) any untested hypothesis or idea” (p. 11). Thus we often hear people say something like “That is just a theory” to discount someone’s explanation and this makes the idea of theory in everyday language appear to be something that is not very useful.

Scholars have a very different idea about what theories are, but this is not to say that all scholars agree on a single definition. To the contrary, there are many definitions of theory used in scholarship (see Tables 1.1 and 1.2). But when we look across all these definitions, we can see three similarities that indicate where scholars generally agree. First, theories are concerned with providing explanations of a field’s phenomenon of interest. Thus they are more than simple descriptions. For example, Littlejohn (1999) argues that the essence of theories is explanation. “Explanation is more than merely naming and defining variables; it identifies reg- ularities in the relationships among those variables. Explanations account for an event by referring to what is going on within the event or between it and some other event. In simplest terms, explanation answers the question, Why?” He con- tinues, “An explanation designates some logical force among variables that makes particular outcomes ‘necessary’ ” (Littlejohn, 1999, p. 23). “Although a simple tax- onomy, or organized list of concepts, may be considered a theory, most scholars would say that this is only a step toward a scholarly theory, which must include some explanatory mechanism or set of propositions that explain how the concepts are related to one another” (p. 957).

While the phenomenon reveals itself through individual elements that are observable to humans, the phenomenon is not any one of these elements or even an assemblage of the elements; the phenomenon is more—it is the pattern of the elements that is not just the What of the phenomenon but also the How and the Why. Theories then are designed initially to capture the essence of the What but

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then must also address the How and Why. This is what is meant by theories moving beyond description and into explanation.

Second, theories are abstracts of some phenomenon, that is, they capture the essence of the phenomenon in a few words relative to the complexity of the phe- nomenon itself. Thus parsimony is important. Theoreticians capture the essence by focusing attention on particular ideas (called concepts) and the relationships (called propositions) among those concepts. Littlejohn (2009) says, “A theory is never intended to reflect the complexity of all experience, but to distill this into a system of knowledge claims explained by a small number of properties. . . . They must reduce complex experience into a manageable set of concepts and proposi- tions” (p. 957).

Table 1.1. Conceptions of Theory Babbie (1998, p. 51):

* A systematic set of interrelated statements intended to explain some aspect of social life Hoover (1984, p. 38):

* A set of interrelated propositions that suggest why events occur in the manner that they do

Infante, Rancer, and Womack (1990, p. 37): * A set of interrelated propositions that suggest why events occur in the manner that

they do Littlejohn (2009, p. 957):

* Human constructions designed to capture what theorists believe the order of the subject matter to be.

* A unified, or coherent, body of propositions that provide a philosophically consistent picture of a subject. The propositions should be generalizable, that is, they should deal with broad patterns in aggregates. They must reduce complex experience into a manageable set of concepts and propositions.

Littlejohn (1999, p. 23): * The essence of theories is explanation, which is more than merely naming and defining

variables. – Explanation is concerned with regularities in the relationships among variables. – Explanations account for an event by referring to what is going on within the event

or between it and some other event. – Explanation answers the question: Why? – An explanation designates some logical force among variables that makes particular

outcomes necessary   McQuail (2005, p. 5): 

* A general proposition, itself based on observation and logical argument, that states the relationships among elements within the observed phenomena

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And third, theories are tools for guidance. That is, they should guide schol- ars toward increasing their understanding of the phenomenon. This means that a theory is a wedge that breaks open the phenomenon in a way that allows scholars to enter and experience it in a meaningful way. As a guide to understanding, the theory guides scholars to insights that resonate with them and lead them to think “Aha that makes sense.” As guides, theories also direct scholars in the creation and analysis of evidence. They stimulate and direct future research (Infante, Rancer, &Womack, 1993) by focusing scholars on what to observe and how to interpret meaning from those observations (Littlejohn, 1999).

Differences. Theories also exhibit differences that have led scholars to put them in different categories (see Table 1.3). However, this classification task is a diffi- cult one because it requires scholars to weight the importance of those differences

Table 1.2. Conceptions of the Purpose of Theory Hempel (1952, p. 1): 

1. To describe particular phenomena in the world of our experience 2. To establish general principles in order to predict and explain experiences

Infante et al. (1993, pp. 45–50): 1. To organize experience 2. To extend knowledge 3. To stimulate and guide further research 4. To predict new things

Littlejohn (1999): 1. To organize and summarize knowledge 2. To map the phenomenon by focusing attention on particular concepts and

relationships 3. To clarify what is observed in order to understand and interpret things 4. To provide guidelines about what to observe and how to observe 5. To predict 6. To provide an open forum for debate and discussion (heuristic function) 7. To share information and insights (communicative function) 8. To control (normative function) 9. To challenge existing culture (generative function)

McQuail (2005, p. 5): 1. To make sense of observed reality 2. To guide the collection and evaluation of evidence

Reynolds (1971):  1. To generate useful scientific knowledge that is abstract (independence of time and

space), intersubjective (agreement about meaning among relevant scientists), and empirically supported (can be compared to empirical findings)

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and when scholars use different weightings or vary in what they consider differ- ences, their categorization schemes vary. Thus the classification of theories has been called “one of the most daunting tasks” because “it defies clear classification” (Littlejohn, 1999, p. 12).

One example of a theory classification scheme was offered by McQuail (2005) who organized mass media theories into five categories: social scientific, cultural, normative, operational, and everyday type theories. McQuail’s social scientific cat- egory includes theories that present general statements about the nature and pro- cesses of a phenomenon in order to guide the systematic and objective observation of the phenomenon so that those statements can be put to the test and validated or rejected by similar methods. The cultural category includes theories that advance arguments that either differentiate cultural artifacts or challenge some practices. The normative category includes theories that present arguments that prescribe how society should be structured or how people should behave. The operational category includes theories that argue for the application of certain practical ideas to solve problems in society. And the everyday category includes theories that are commonsense principles that people generally use to guide their behavior and thinking.

Table 1.3. Types of Theories Reynolds (1971): 

1. Set of laws—the conception of scientific knowledge as a set of well-supported empirical generalizations or laws

2. Axiomatic—an interrelated set of definitions, axioms, and propositions that are derived from axioms

3. Causal process—a set of descriptions or causal processes McQuail (2005): 

1. Social scientific—offers general statements about the nature and processes of a phenomenon that guide the systematic and objective observation of the phenomenon so that those statements can be put to the test and validated or rejected by similar methods

2. Cultural—advances arguments that either differentiate cultural artifacts or challenge some practices

3. Normative—presents arguments that prescribe how society should be structured or how people should behave

4. Operational—argues for the application of certain practical ideas to solve problems in society

5. Everyday theory—commonsense principles that everyday people use to guide their behavior and thinking

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Another way to organize theories by type was suggested by Reynolds (1971) who arranged theories according to the nature of their propositions into three categories of set of laws, axiomatic, and causal processes. His set of laws category includes theories where the conception of scientific knowledge is a set of well-sup- ported empirical generalizations or laws. The axiomatic category includes theories that present an interrelated set of definitions, axioms, and propositions that are derived from axioms. And the causal process category includes theories that pres- ent a set of descriptions or causal processes.

Types of Theories: Advocacy and Scientific

Within the field of communication, a useful way to categorize theories is to make a distinction between advocacy theories and scientific theories. An advocacy theory presents a thesis position then assembles evidence in a compelling argument to support that thesis. The thesis can be an ideology (such as Marxism or feminism) or a perspective (such as psychoanalysis). In contrast to advocacy theories, scien- tific theories present a set of explanatory propositions that are speculations about the phenomenon that require testing to determine their value. Scientific theories are less concerned with winning an argument than with refining their explana- tions so that they better fit the patterns within the phenomenon itself as revealed through empirical testing. (For more on this distinction, see Potter, 1996.)

While all theories present claims that purport to explain something about a phenomenon, advocacy theories differ from scientific theories in three major ways—the purpose of the theory, the use of evidence to support the theory, and the criteria for quality in judging a theory.

Contrasting by purpose. The purpose of advocacy theories is to present a par- ticular thesis as an explanation of the phenomenon then convince readers of the value of that explanation. Thus the purpose is to win an argument over other schol- ars who argue for other theories. Knowledge is generated by arguments based on illustrating that certain perspectives—or ideologies—can produce novel insights that are interesting and useful. These scholars argue that their perspective on the phenomenon works well to reveal a different way of thinking about a phenomenon that readers have likely been taking for granted or have a faulty and/or limited understanding of because of the limitations imposed by the status quo perspec- tives they have been using in the past. Scholars select evidence to support their claims and fashion their arguments in a way to maximize the persuasiveness of their arguments.

In contrast, the purpose of scientific theories is to test explanations rather than to select one explanation then argue for its value. Scientific theories require

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researchers to gather evidence not for the purpose of supporting their claims (although they often hope that the evidence will do so) but instead to test their claims. When the gathered evidence fails to support their expectations (hypoth- eses), researchers must continue testing that claim by either (a) running another test to determine if the preponderance of evidence gathered in many different tests tends to add support to their claim, or (b) alter their claim to bring it into line with the results of the nonsupporting empirical evidence then run additional tests to determine if the altered claim achieves a greater degree of support. Thus a key purpose of scientific scholarship is to be progressive, that is, scientists believe that each test provides scholars with insights about how to improve either by altering speculations or by designing subsequent tests with fewer flaws.

Contrasting by treatment of evidence. Scholars who use advocacy theories look for evidence to support their position so as to maximize the strength of their argu- ment. When they encounter evidence that weakens or refutes their position, they either ignore it or else critically analyze it to try to uncover some aspect of it that they can argue is faulty in some way.

In contrast, scholars who use scientific theories begin with tentative expec- tations in the form of hypotheses that they operationalize from a general claim in a theory. They then design an empirical test to generate fresh findings. If those findings support their hypotheses, then researchers conclude there is support for the theoretical explanations from which the hypotheses were operationalized. But if those empirical findings fail to support their hypotheses, then researchers con- clude that the theoretical explanations have been falsified. Thus they are not trying to win an argument but to increase knowledge about the phenomenon by trying to conduct a test of the theory’s claims in an unbiased a manner as possible. That is, researchers try to keep an open mind and allow the findings of their empirical studies to emerge even if those findings run counter to their initial expectations. So when the results of empirical tests fail to support a claim made by a theory, those results are still acknowledged, but those results that do not support the the- ory are expected to reshape the claims made by the theory so that through this long-term process of accommodating patterns of support and falsification, the set of claims made by the theory become more precise and useful explanations of the phenomenon.

Contrasting by criteria for judging quality. The value of advocacy scholarship lies in how well the user of the theory constructs a supporting argument. For example, prosecuting attorneys have a theory of a case that the accused commit- ted the crime, so they comb through the evidence to select the strongest bits that support their argument for guilt. Prosecutors then assemble those observations (by witnesses, crime scene investigators, pathologists, etc.) into a coherent argument

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that supports their theory of the case. Defense attorneys sort through the same body of evidence but they are looking for elements to support a different the- ory—that is, that their client is not guilty. Defense attorneys then assemble the bits that support their theory into the strongest argument they can make. Juries then are empaneled to make judgments about which side has presented the higher quality case.

Some humanistic scholars conduct textual analyses where a theory (e.g., Marxist theory, feminist theory, psychoanalytic theory) guides them about how to interpret the text to arrive at particular claims that explain that text. Then they observe particular elements in those texts and select only those that best support their claims.

In contrast, scientific theories establish their quality through meeting a sequence of three criteria. First, theories need to stimulate tests of their claims. Second, the more the results of those empirical tests support the claims in the theory, the stronger the explanatory value of that theory. And third, the more that theories can accommodate the growing patterns of empirical results, the better the theories grow in precision and validity.

In summary, there are many definitions of theory but fundamentally, they all share certain characteristics. Those definitions all regard theories as focusing atten- tion on some phenomenon of interest, providing a system of explanation of that phenomenon in a parsimonious way, and delivering guidance to scholars that helps them understand the phenomenon, collect evidence, and interpret the meaning of that evidence. There are also many different kinds of theories with the most essen- tial distinction being between advocacy theories and scientific theories. Because most of the work in the field of media effects has been of a scientific nature, we narrow our focus onto scientific theories.

Components of Scientific Theories

There are five components to scientific theories. They are: concepts, propositions, axioms, calculus, and model. The first two of these are the most salient, that is, scholars who write about a particular theory typically focus on that theory’s con- cepts and propositions.

1. Concepts. Concepts are the building blocks of theories (Babbie, 1998; Littlejohn, 2009; Shoemaker, Tankard, & Lasorsa, 2004). “A concept is a category or class of objects, events, situations, or processes designated by a term. A concept encompasses a group of things that share one or more attributes” (Littlejohn, 2009, p. 957).

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Some concepts are primitive while others are derived. Primitive concepts are those terms that are treated as though everyone knows the definition. These are words that people use in their everyday lives and have no trouble assuming that oth- ers know their meaning (e.g., person, car, breakfast, weather). Some are easy to define (e.g., individual, woman, tree, eye). Other terms are derived; these must be defined because not everyone would know what they mean (e.g., equifinality, cybernetics, face behaviors) or because the meaning is different from how most people would nor- mally define them (e.g., cultivation, framing, dissonance, priming, accommodation).

A special type of derived concept is the construct. There are three types of con- structs. First is the ideal type (e.g., utopia, infinity, eternity), which are things that must be imagined rather than observed. Second, there are hypotheticals (e.g., atti- tudes, beliefs, values), which can never be observed directly so scholars hypothesize that they exist and must therefore define what they are and how we can attribute evidence for their existence. For example, aggression is a hypothetical construct that can be defined as a drive to perform harmful behaviors. Given this definition, we cannot observe a drive directly but we could argue that evidence for aggression includes things like children hitting a doll or yelling at a playmate. Third, there are constructions (e.g., socioeconomic status [SES] or intelligence). These are an amalgamation of ideas constructed in a particular way by scholars. For example, one scholar might use a construction of SES as people’s household income plus their income level while another scholar might use a construction of SES as peo- ple’s individual hourly wage times hours worked per year minus personal expenses plus years of college completed.

Reynolds (1971) points out that “To refer to any set of abstract concepts used to describe a phenomenon as a theory is an inappropriate use of the word if only a set of concepts is presented” (p 11). He says that a scientific theory also needs statements showing how the concepts interrelate as an explanation of that phenomenon.

2. Propositions. Propositions are relational statements that make claims about how two or more concepts are associated with one another either by covariance or causally (Babbie, 1998; Reynolds, 1971).

Propositions vary in generality, that is, the scope of their claims. When a prop- osition claims a relationship between two concepts, it is typically very general. However, as theoreticians add qualifiers or contingent conditions to their prop- ositions, those statements are reduced in generality. For example, the claim that viewing violent media messages is associated with subsequent aggressive behavior is very general because as expressed, it applies to all violent messages, all peo- ple, at all times, and in all situations. If this claim were modified to say “viewing

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violent media messages is associated with subsequent aggressive behavior if the violence is portrayed as being perpetrated by characters who are attractive, justified in their actions, and rewarded” then the proposition is narrower in scope because it excludes certain types of portrayals. Propositions in scientific theories are more valuable when they are more general because they have greater scope; however, if the patterns of testing such a proposition show that it does not hold at such a general level, then the proposition loses its value until it is refined to account for the qualifying conditions.

3. Axioms. Axioms are the fundamental assumptions theoreticians make in order to support their theories. Babbie (1998) says that theories have a foundation in an axiomatic groundwork, which are fundamental assertions assumed to be true. Thus axioms are statements of theoreticians’ beliefs upon which they construct their explanations.

Some of these assumptions can be tested to see if they hold while other assumptions cannot. For example, values are assumptions that cannot be tested and therefore cannot be confirmed or discredited, so they must be accepted. Some people believe there is a god who created the entire universe in one week and who is everywhere observing the behavior of everyone and making judgments about each individual’s suitability to be accepted into a heaven after physical death. People who hold this belief accept it on faith rather than from proof. There is no adequate way within the human experience that people can acquire proof of the validity of this belief.

Scholars hold deep philosophical beliefs, such as ontology and epistemology. Ontology refers to beliefs about the existence of things, while epistemology refers to beliefs about how humans can make sense of their experiences. For example, some scholars hold an epistemological belief that humans are fundamentally lim- ited in their perceptions so they will never be able to experience entities external to them accurately. In contrast, other scholars hold an epistemological belief that humans can distance themselves from phenomenon (including social phenomena) enough so that their observations are an objective viewing of that phenomenon.

Some axioms can be tested. When they are found to hold, the theory has a stronger foundation. However, when they are found to be faulty, the theoreticians are under pressure to alter or replace that axiom. A common example of this is the nature of definitions of key concepts. When theoreticians invent a new concept, they provide an initial definition that they believe at the time to be the best way to define the concept. However, this definition is likely to be found faulty over time as research accumulates. For example, there are theories that use the concept of gender but define it as biological sex, and this illustrates an assumption by a the- oretician that all females are the same, that all males are the same, and that there

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are significant differences between the two groups. While this distinction holds relatively well in biology, it does not hold as well in the social sciences. Biologists have evidence of distinct differences between males and females with sex organs, hormone production, and ability to reproduce. However, within the social sciences, evidence continually shows that many females exhibit male category behaviors and that many males exhibit female category behaviors. For example, many people assume that males are more aggressive than females so that violent video games are only played by males. But research has shown that many players of violent video games are female and that many females are more aggressive than many males.

Slife and Williams (1995) point out that all theories are based on a foundation of assumptions “and these assumptions are most often not explicit.” They continue “assumptions always lead to implications,” which are “the consequences of an idea or theory—the conceptual costs, calculated in terms of other ideas that logically flow from it, that we are logically obligated to accept” (p. 17). They say that “any theory explains some things, but leaves many things still to be explained. These unexplained things and the implications of the theories are important, yet most often, implicit, and theorists do not usually deal with them. Only if we become aware of these implicit ideas as problems to be dealt with can we deal with them” (pp. 17–18).

4. Calculus. Scientific theories can never be tested directly because of the gen- eral nature of the concepts and propositions. The concepts need to be translated into measures, and the propositions need to be translated into hypotheses. This translation process is called operationalization. The rules of operationalization are the calculus of the theory. The calculus is a set of transforming rules by which one class of ideas (theoretical concepts) can be transformed into another class (testable variables).

The calculus is not typically addressed explicitly by theoreticians. Usually the calculus is revealed through the patterns of design decisions made by the theore- ticians when they conduct empirical studies to test the claims they have made in their theories.

5. Model. The terms “model” and “theory” are sometimes used as if they were interchangeable, but this is faulty. Slife and Williams (1995) point out why there is a major distinction by saying that models display an organization of concepts—a sequence or structure that helps scholars think about components or a sequence. Models are typically graphical in display, with boxes for concepts and arrows indicating how the ideas in the boxes are related to one another. If the model is supported with definitions for the concepts and a narrative explaining how the concepts are related, then the model is part of a theory. That is, a model is not itself a theory, because it does not include enough components to qualify as a theory.

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A model can take the form of flow charts, graphics, pictures, icons, or mathe- matical equations. Models do not add any new information to the theory beyond the propositions; instead, models deliver their value as a graphical display of the system of explanation that is captured in narrative form by the propositions.

Life Cycle of Scientific Theories

The development of scientific theories follows a life cycle pattern of creation, growth, and decline.

1. Creation. When scholars create theories, they rely on a combination of speculation and evidence. Sometimes the creation relies more on speculation and other times it relies more on evidence.

The evidence-focused method has been referred to as grounded theory, which follows the classic inductive method of science. Scholars collect observations, look for patterns across individual observations, then argue that those patterns are likely to apply to larger aggregates beyond the sample of observations from which those patterns were inferred. This process is explained in detail by Glasser and Strauss (1967) in a book entitled The Discovery of Grounded Theory in which they provided a rationale and method for moving beyond simply describing data generated in empirical studies to making general statements about the phenomena being exam- ined. The authors show how patterns are discovered then provisionally verified through systematic data collection and analysis of data pertaining to that phe- nomenon. Therefore, data collection, analysis, and theory stand in reciprocal rela- tionship with each other. Using the process of grounded theory, a scholar does not begin with a theory then collect evidence to support its claims. Rather, a scholar begins with an interest in examining a part of a phenomenon, then makes obser- vations so that patterns are allowed to emerge unhampered by a priori expectations (Strauss & Corbin, 1990).

In contrast to the inductive method, which begins with observations, some scholars begin with speculation. These scholars create a set of claims as a tentative explanation for some part of the phenomenon they want to examine, then they design research studies to test their claims (Shoemaker et al., 2004). Such the- ories typically start as implicit understandings about the way things work, that is, they grow out of folklore, traditional wisdom, and common sense (Severin & Tankard, 2000). These theories start out as claims that are often simple aphorisms or maxims. But speculation is not enough to explain some part of a phenomenon to scientists; they need to test their claims to see if they can be supported with empirical evidence.

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2. Growth. Whether a theory originates as a tentative set of speculations to explain a problem or arises from a perception of a pattern in a collection of data, the theory needs to develop if it is to become a useful system of explanation. This development typically follows one of three methods, as Kuhn (1970) has argued in his The Structure of Scientific Revolutions. First, theories can grow by extension, that is, theories add more concepts and propositions over time in order to explain more of a phenomenon. Second, theories can grow by intention, that is, theories develop a deeper and more precise understanding of the original concepts and propositions. Third, they develop through a radical reformulation such as a revolu- tion in thinking, that is, old assumptions are rejected and new assumptions require scholars to accept a big change in concepts and propositions.

Regardless of the pattern of development, theories increase in value when they grow in terms of precision, utility, and/or explanatory power.

a. Growth in precision. Increases in precision refer to improvements in the con- ceptual clarity of the definitions of concepts and in the articulation of propositions. When fields are new, theoreticians’ claims are fuzzy rather than precise, because the claims are based on guesses about the nature of a phenomenon, its components, how those components should be conceptualized, and how those components work together in a system of explanation. Over time, as a literature of tests grows, the contours of support and nonsupport begin to become clearer. The precision in the growth of a theory is keyed to the theoretician’s ability to perceive patterns in the empirical literature and to make alterations to their claims so that the faulty areas in their system of explanation are replaced. When theoreticians use these patterns of findings to alter their definitions of concepts and reconfigure their set of proposi- tions, their theories grow in precision. As Hempel (1952) writes, “In the initial stages of scientific inquiry, descriptions as well as generalizations are stated in the vocab- ulary of everyday language. The growth of a scientific discipline, however, always beings with it the development of a system of specialized, more or less abstract, con- cepts and of a corresponding technical terminology” (Hempel, 1952, p. 1). Hempel continues: “It is, therefore, of paramount importance for science to develop a system of concepts which is suited for the formulation of general explanatory and predictive principles” (p. 20). He says the “vocabulary of everyday discourse, which science has to use at least initially” (p. 20), loses its value over time as scholars’ understanding of the phenomenon grows and requires a greater degree of precision.

The precision of a theory also increases when theoreticians make their proposi- tions more operative. Propositions become more operative as theoreticians increase the clarity expressing the relationship among concepts. For example, consider the proposition: “A is related to B.” This expresses a relationship between two concepts

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but does not clarify what that relationship is. The proposition “A is related to B in a positive linear fashion” is more operative than the first proposition because it specifies a relationship with more precision. And the proposition “A is related to B in a positive linear fashion with young children but with adults the relationship is linear and negative” displays an even greater degree of precision because it spec- ifies an age contingency.

b. Growth in utility. Utility is keyed to the degree to which theoreticians accom- modate patterns that emerge through empirical testing. Oftentimes, the results of empirical tests will not support the claims made in propositions. When this occurs, their theories lose utility if theoreticians ignore the discordant findings; in con- trast, when theoreticians make alterations to their propositions to accommodate the newly found patterns, then the theories increase in utility.

Utility is related to precision in research. Research studies are more useful when the designers of empirical tests have made design decisions that take max- imum advantages of strong elements in the literature and avoid the weaknesses and flaws. Weaknesses are those design options that do not work as well as other options (for more detail on this, see Potter, 2018). For example, if there are mul- tiple ways to measure a concept, designers of a research study exhibit higher pre- cision when they demonstrate that the measure they are using is more valid than the alternatives. Flaws are design decisions that do not serve the purpose of the study or that contradict other design decisions. For example, designers who want to make claims about the prevalence of something in the general population might generate a nonrepresentative sample; this is a flaw because a nonrepresentative sample cannot be used to identify patterns that can be generalized from the sample to the population of interest.

c. Growth in explanatory power. Explanatory power refers to the degree to which the claims made in the theory have generated empirical findings that sup- port those claims. Early tests of a claim often result in equivocal support. When this happens, theoreticians can ignore these patterns and it is likely that additional tests will also find equivocal support. Alternatively, theoreticians can analyze the patterns of equivocal support and find a way to alter their claims to make them more precise. Typically, a pattern of equivocal support for a claim indicates the need to consider contingencies, that is, the claim might hold for only one type of person, place, time, or message. When theoreticians then alter their general claims to recognize contingencies, the pattern of support can increase. Remember the example above “A is related to B.” Let’s say that the empirical tests of this claim show a pattern where some tests show that there is no relationship, some tests show that the relationship is positive, and some tests show that the relationship is negative. If the theoreticians are able to see a pattern in the findings that can be

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traced to age, for example, then they can alter their general proposition to account for the influence of age and subsequent tests will avoid weak (r =  .00) findings where the results from children and adults are aggregated into a nonmeaningful average and instead show that the relationship is positive among children and at the same time negative among adults.

3. Decline. Scientific theories go into decline when theoreticians fail to alter their systems of explanation in response to emerging patterns in the empirical lit- erature, criticisms of the theory, and changes in the phenomenon being explained. Let’s examine each of these three in some detail.

Rarely will an empirical test provide unqualified support for the general claims made by a theory. More typically empirical tests will result in relatively weak or equivocal support for general claims. In this common situation, theoreticians have two options. One option is for theoreticians to alter their propositions to make them better reflect the patterns of findings from empirical testing. A second option is for theoreticians to defend their claims and blame weaknesses in the empirical tests for the pattern of weak support for the general claims in their theory. The second option is typically used by theoreticians but this option limits the growth of the theory. Blalock (1984) warns that it is often difficult to tell if a failed test is really a good test of the theory because there are so many factors that are in play, and that many theories are untestable as they are currently formulated.

Theories also need to respond to criticisms. This does not mean that theo- reticians need to make all the changes that critics suggest; instead it means that theoreticians need to acknowledge the criticism and use it as a forum for dialog. By engaging in dialog, theoreticians can learn more about what is really bothering the critics and alter the theory’s claims when the theoreticians feel those changes will strengthen the theory or not make the changes they feel will weaken the theory. But either way, theoreticians who fail to engage with the criticism create an artifi- cially low ceiling on the growth of their system of explanation.

Finally, some phenomena change over time. If a theory that purports to explain that phenomenon does not change, then it loses its ability to explain that phenomenon. This is especially the case with a phenomenon that is as dynamic as media and their effects.

Conclusion

The purpose of scholarly fields is to generate knowledge about that field’s phenom- enon of interest then to share that knowledge. The most valuable tool in fulfilling this purpose is a good theory. Theories differ from one another in many ways; when

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we focus attention on how theories differ in purpose, treatment of evidence, and criteria for quality, it is useful to organize theories into two general categories of advocacy theories and scientific theories. This book focuses attention on scientific theories, not because I am arguing that scientific theories are better than advocacy theories; instead, the book focuses on scientific theories because the media effects literature is dominated by scientifically based scholarship.

Scientific theories begin as systems of explanation constructed from a combi- nation of speculation and patterns from the empirical literature. Over time as the theory’s claims are tested, those claims can increase in value when they increase their precision and explanatory power. Or those claims can decline in value if they fail to attract research interest in testing them or when tests fail to support the theory’s claims and the theoreticians ignore the need to alter the claims.

To the extent that theories grow in precision and validity over time, useful knowledge grows. But when theories fail to increase the precision of their concepts and propositions, when they fail to eliminate axioms that are found to be faulty, and when they fail to alter their systems of explanation to account for patterns in empirical testing, they lose their potential utility. And a scholarly field that is guided by theories with low precision and weak validity will struggle to provide a progressively useful system of explanation about the field’s focal phenomenon. Blalock (1984) writes, “One of the basic premises of scientific research is that one proceeds by eliminating or modifying those theories that fail to make correct predictions” (p. 138). He argues that when a field does not eliminate inadequate theories, the field becomes cluttered with alternatives and “once the alternative theories become sufficiently numerous, it also becomes so difficult to attempt syn- theses—or even summaries—that no one makes the effort. Each theory is studied superficially” (p. 140).

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