Theory Words & Definitions

There are a lot of terms that get thrown around in the academic lexicon, sometimes they align with those you’ll find in a dictionary, sometimes they don’t. So I thought I’d outline a good handful for you here that will be helpful as you wade through some sweet, delicious mass comm theories (Fig. 1). This article is based on Reynolds’s book: a primer in theory construction (a must have for aspiring theorists), citation at the end of the article, as well as from a grad class I took.

a primer in theory construction by paul davidson reynolds
Fig. 1: Sweet, delicious mass comm theory… and a book.

Object of analysis: The system whose properties we are trying to explain. The research problem should determine what attributes of the system we are interested in.  If the attributes are those of the individual person (e.g., a personality characteristic, attitude change), then it probably belongs to cognitive theory. If the attributes are those of a group of persons (e.g., community status, rate of diffusion), then it lies in the social systems realm. Societies, communities, large organizations, and primary groups are types of social systems.

Concepts: The most basic elements in theory, they are the attributes of the object that we are trying to explain and those that we are using to provide the explanation. They are abstractions from reality. We also use them in everyday life, of course, but research concepts are supposed to be more precise. Concepts are interesting to researchers only when they vary; we call a concept that can be observed to have different values a variable (as contrasted to a constant).  Often called constructs because scientific concepts are carefully constructed from observation.

Conceptual definition: Each concept in a theoretical system (a collection of interrelated theoretical statements) should have a clear and unambiguous definition that is consistently used by the individual theorist and in agreement with the way other theorists define the concept. But that is seldom the case in social science. Careful definition of concepts is where we must begin with theory building (Normally I hate italics, but dammit, that sentence is important, write it down!)

Postulates:  Ideas, biases, and strategies of a particular theorist that help to explain why his theory is constructed as it is and why he does the kind of research he does (nothing to do with posteriors). Theses statements are more abstract than assumptions or theoretical statements and not usually testable. They may represent statements about human nature, causation, the nature of data, and the broad type of causal forces in society – in short, what’s important to look at and how you should do it.

Assumptions: These are statements about the concepts used in the theory.  Assumptions are taken for granted in the theory being tested. They are not investigated, but the falsification of that theoretical statement may result in the revision of the assumption in the future. Assumptions (or revised assumptions) may serve as hypotheses in subsequent research. Two or more assumptions provide the premises from which the theoretical statements (and hypotheses) are derived through logic.

Theoretical Statement: The statement specifying the relation between two or more concepts (variables). Reynolds calls these relational statements and distinguishes these from existence statements that include postulates, definitions and assumptions. Other people call theoretical statements axioms, theorems or propositions. Seriously, the label doesn’t matter, just so we know what we’re referring to.

Relations: (No not that kind, get your mind out of the gutter) The connection between concepts can be stated in a number of forms: that one variable causes another, that two variables are associated, and more complicated relations are possible.

Operational definitions: The set of procedures a researcher uses to measure (or manipulate as in experiments) a given concept. These should follow clearly and logically from the conceptual definition of the concept. These are less abstract than conceptual definitions. They tell us “how to measure it,” ideally using more than one method.

Explication: The process by which conceptual and operational definitions are connected. This is done either by analysis using the logical criteria of definition or through empirical analysis using research data to clarify measurement to distinguish the concept from other concepts. Abstract concepts often need to be broken down into two or more lower order (less abstract) concepts before they can be translated into hypotheses. Basically a fancy way of saying “explain.”

Measurement: The assignment of values to objects on the basis of rules relevant to the concept being measured.  Reynolds describes four levels of measurement: nominal, ordinal, interval, and ratio. The quality of measurement is assessed by reliability and validity. Speaking of reliability…

Reliability: The stability and precision of measurement of a variable.  Stability overtime is called test-retest reliability (i.e., do those scoring high at one time also score high at a second point in time). A second form, equivalence, looks at the level of agreement across items (internal consistency) or forms, or between coders doing the measurement.

Validity: The degree to which you’re really measuring what you think you’re measuring. There are two different approaches: you find external independent evidence (e.g., a criterion group known to possess the characteristic) against which to compare your measurement (pragmatic validity), or you look at the extent to which the empirical relationships of the concept to other concepts fit your theory (construct validity).

Hypothesis: A statement of the relationship between two or more operational definitions. It should be capable of being stated in an “if, then” form, and is less abstract than theoretical statements, assumptions, and postulates. The type of research you are doing will largely dictate how to phrase your hypothesis.

Dependent Variables + Independent Variables: The dependent variable is the “effect” that we are seeking to explain; the independent variable is the presumed “cause” of that effect. We often say “x” is the independent variable that is the cause of the dependent variable “y,” (the effect). There are various names for third variables: extraneous variable, intervening variable, mediating variable, etc. that alter the relationship between the independent and dependent variables.

Good. Good. Let the empirical testing flow through you.

Empirical testing: A good theory must be capable of being tested by observation in the “real world.” Most frequently, statistics are used to make this test. Note that we test theory indirectly through hypotheses and operational definitions. It is made even more indirect by the fact that we test the null hypothesis: the statistical hypothesis of no difference – that the relationship is not strong enough to reject chance. If the data is judged to be not strong enough to reject the null hypothesis, then we have falsified the theoretical statement. If the observations are judged sufficient to reject the null hypothesis, then theory merely remains viable or tenable.

Type I and Type II errors: One of the problems of doing research is that you can be wrong in the inferences you make from research evidence. You can be wrong if you decide to reject the null hypothesis and say that the result is consistent with your theory. That’s a type I error. If your results don’t look very supportive and you decide you can’t reject the null hypothesis, you can be wrong too. In that case you incorrectly gave up on your research hypothesis (indirectly falsifying your theory), but there really was support in the “real world” and your research wasn’t good enough to detect it. That is a type II error.

Causality: As you may know by now, this is a “can of worms.” It’s probably better to think of establishing causality between two variables as something that we move toward than to think of it as being capable of being “discovered” through an experiment. Realize that it is better to think in terms of various types of causes than to look for “the cause” of something. To work toward causality, three conditions have to be met: There has to be an association (correlation) between the two variables; a time order has to be established such that the presumed cause precedes the effect; and other explanations have to be ruled out, such as that some third variable causes both of the two variables of interest. If this last is the case, then we say the relationship we thought was causal was really spurious.

Necessary condition: A situation that must be present for some effect to take place. This is one type of cause. Sometimes a necessary condition describes the level of a third variable that is essential for the relationship between two other variables to hold. In this case the third variable can also be called a contingent condition. Third variables that make the relationship stronger or weaker but don’t totally limit its domain (are not necessary conditions) are called contributory conditions.

Sufficient condition: A situation that if present is enough to produce all effects. This implies that there are no contingent conditions. Experiments are probably more suited to finding sufficient conditions than are nonexperimental sample surveys and other methods. Social scientists would like to find necessary and sufficient conditions, but that is a goal, not an immediate reality.

Models and paradigms: Social scientists sometimes find it useful to employ simplified versions of reality to gain insight and to illustrate their theoretical ideas. A model is a conceptual structure borrowed from some field of study other than the one at hand; it needs not include causal statements, but it does specify structural relationships among variables. A paradigm is a conceptual structure designed specifically for the field of application; it also specifies structural relationships. When a model or paradigm incorporates causal statements, it is usually called a theory. Models and paradigms can be assessed on the basis of their usefulness in helping us construct valid theory.

Reynolds, P. D. (1971). A primer in theory construction. Indianapolis, IN: Bobbs-Merrill Educational Publishing.

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Quiet Down, here’s Spiral of Silence

spiral of silence shhh
Nothing like a good 'shhhh' stock image.

Originally proposed by German political scientist Elisabeth Noelle-Neumann in 1974, Spiral of silence is the term meant to refer to the tendence of people to remain silent when they feel that their views are in opposition to the majority view on a subject. The theory posits that they remain silent for a few reasons:

  1. Fear of isolation when the group or public realizes that the individual has a divergent opinion from the status quo.
  2. Fear of reprisal or more extreme isolation, in the sense that voicing said opinion might lead to a negative consequence beyond that of mere isolation (loss of a job, status, etc.)

For this theory to be plausible it relies on the idea that in a given situation we all possess a sort of intuitive way of knowing what the prevailing opinion happens to be. The spiral is created or reinforced when someone in the perceived opinion majority speaks out confidently in support of the majority opinion, hence the minority begins to be more and more distanced from a place where they are comfortable to voice their opinion and begin to experience the aforementioned fears.

The spiral effect is experienced insomuch as this activates a downward spiral where fears continually build within the minority opinion holder, hence the minority opinion is never voiced. Since it’s appearing on this blog you could assume that the theory posits that the mass media has a effect on this process, if you’re assuming that… you’re right on. The media plays an important role in this process, especially in dictating or perceptually dictating the majority opinion.

The closer an individual feels their opinion resides to the held majority opinion the more likely they are to be willing to voice it in public discourse. A few other important tenets to mention: this theory relies heavily on the idea that the opinion must have a distinct moral component (i.e. abortion, legalization of _______ ), no one will experience the spiral of silence trying to talk out what toppings to get on their pizza with roommates.

The theory has some weaknesses or at least points of contention, two of the most notable are those of the vocal minority and the internet. The internet (a.k.a. interwebs, series of tubes – thanks, Al) seemingly levels the playing field, where a minority opinion won’t be felt by the individual as a minority opinion and might be voiced in that arena whereas the individual would have not been so vocal in in other place of public discourse.

There you have it… Spiral of Silence. Don’t spend it all in one place.

Resources:

University of Twente lists some major pubs regarding the theory. So does Wikipedia, but no one cares. Here are Twente’s:

  1. Glynn, J.C., Hayes, F.A. & Shanahan, J. (1997). “Perceived support for ones opinions sand willingness to speak out: A meta-analysis of survey studies on the ‘spiral of silence’” Public Opinion Quarterly 61 (3):452-463.
  2. Glynn, J.C. & McLeod, J. (1984). “Public opinion du jour: An examination of the spiral of silence, “ Public Opinion Quarterly 48 (4):731-740.
  3. Noelle-Neumann, E. (1984). The Spiral of Silence: Public Opinion — Our social skin. Chicago: University of Chicago.
  4. Noelle-Neumann, E. (1991). The theory of public opinion: The concept of the Spiral of Silence. In J. A. Anderson (Ed.),Communication Yearbook 14, 256-287. Newbury Park, CA: Sage.
  5. Simpson, C. (1996). “Elisabeth Noelle-Neumann’s ‘spiral of silence’ and the historical context of communication theory.” Journal of Communication 46 (3):149-173.
  6. Taylor, D.G. (1982). “Pluralistic ignorance and the spiral of silence: A formal analysis,” Public Opinion Quarterly 46(3):311-335.
  7. See also: Kennamer, J.D. (1990). “Self-serving biases in perceiving the opinions of others: Implications for the spiral of silence,” Communication Research 17 (3):393-404; Yassin Ahmed Lashin (1984). Testing the spiral of silence hypothesis: Toward an integrated theory of public opinion. Unpublished dissertation, University of Illinois at Urbana-Champaign.

Cultivation Theory: How Violence Might Affect Us

Originally proposed by Gerbner & Gross (1976 – Living with television: The violence profile. Journal of Communication, 26, 76.) Cultivation theory states that high frequency viewers of television are more susceptible to media messages and the belief that they are real and valid. Heavy viewers are exposed to more violence and therefore are effected by the Mean World Syndrome, the belief that the world is a far worse and dangerous place then it actually is.

She's been watching too much TV

According to the article the heavy viewing of television is creating a homogeneous and fearful populace. If one were to count the number of studies done on TV violence and its effect on viewers you would be reading articles when the Republicans take back the White House and long after. It is by far one of the most studied topics in mass comm research. Why you ask? Because it is one of the most hot button issues within society. And guess what they have learned? That results are inconclusive. Apparently with more information comes less clarity. No one really knows how or even if violence on TV or in film negatively or positively affects its views. They think they know, but you’ll get different answers depending on who you talk to.

Continue reading “Cultivation Theory: How Violence Might Affect Us”

The Agenda-Setting Function of the Mass Media

mass comm theory booksBy now most people who study mass communication have heard of agenda setting theory. It was first put forth by Maxwell McCombs and Donald Shaw in Public Opinion Quarterly (you can download the full article here). They originally suggested that the media sets the public agenda, in the sense that they may not exactly tell you what to think, but they may tell you what to think about. In their first article where they brought this theory to light their abstract states:

In choosing and displaying news, editors, newsroom staff, and broadcasters play an important part in shaping political reality. Readers learn not only about a given issue, but also how much importance to attach to that issue from the amount of information in a news story and its position. In reflecting what candidates are saying during a campaign, the mass media may well determine the important issues—that is, the media may set the “agenda”of the campaign.

McCombs and Shaw went on to write on agenda setting at great length, the have produced many articles and research on the various facets of the theory. Since their introduction of this theory there has been a plethora of research regarding its uses, and their now exists an extension of the theory called Second Level Agenda Setting. Of all mass comm theories, this one is one of the most beaten to death. Continue reading “The Agenda-Setting Function of the Mass Media”

What is Theory?

Let’s think about this… I realize that as I get this blog off of the ground I may have missed one of the most important questions of all when it comes to Mass Communication theory. What exactly is it and what is it supposed to accomplish? As a basis for moving forward and creating a common ground from which we must all start, a foundation must be built before we can jump in to talking about the various theories and models Mass Comm scientists use. Let’s begin:

What is the goal of theory? Theory strives to formulate statements or propositions that will have some explanatory. This is our most basic definition and generalized way of looking at theory. Continue reading “What is Theory?”