Diffuse Status Characteristics and the Spread of Status Value: A Formal Theory

by Joseph Berger, M. Hamit Fis¸ek
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Diffuse Status Characteristics and the Spread of Status Value: A Formal Theory
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Joseph Berger, M. Hamit Fis¸ek
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2006
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The American Journal of Sociology
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Diffuse Status Characteristics and the Spread of Status Value: A Formal Theory1

Joseph Berger

Stanford University

M. Hamit Fis¸ek

Bog˘azic¸i University

The authors present a formal theory of the social construction of diffuse status characteristics. The theory is formulated within the framework of earlier work on status construction by Ridgeway and others and uses the mathematical framework of the theory of status characteristics and expectation states. This theory describes how an initially nonvalued characteristic can acquire status value and generalized expectation states from its association with already established and valued status elements. The authors derive eight theorems from their theory that describe different conditions under which the initially nonvalued characteristic acquires such status value. They consider illustrative applications of the theory and some research that is relevant to the formulation. The authors then conclude with a discussion of the implications of their formulation for the general understanding of status organizing processes.

INTRODUCTION

The original status characteristics theory was formulated to provide an account of how individuals use status information such as gender, race, and occupational position to form expectations for each other and for how these expectations determine their behavior. The primary concern was with the behavior of individuals in goal-oriented situations in which they were collectively oriented to each other and the task (Berger, Cohen, and Zelditch 1966, 1972).

While the original formulation is restricted to situations where there

1 We would like to acknowledge support for Joseph Berger’s work from the Hoover Institution and for M. Hamit Fis¸ek’s work from the Turkish Academy of Sciences. Direct correspondence to Joseph Berger, Department of Sociology, Stanford University, 450 Serra Mall, Stanford, California 94305-2047. E-mail: jberger@stanford.edu

� 2006 by The University of Chicago. All rights reserved. 0002-9602/2006/11104-0003$10.00

1038 AJS Volume 111 Number 4 (January 2006): 1038–79 are only two actors and only a single diffuse status characteristic is operating, there have been extensive elaborations of the theory. These extensions enable us to deal with situations that involve multiple status characteristics (whether they are consistently or inconsistently allocated), situations in which actors can form status-based expectations for rewards, and situations where actors can interact across a sequence of different tasks with different others who may possess different status distinctions (Berger et al. 1977; Berger et al. 1985; Berger, Fis¸ek, and Norman 1989).2

A key concept in the theory of status characteristics and expectation states is that of a diffuse status characteristic. The structure of a diffuse status characteristic can be said to involve four major features: (1) a socially significant characteristic such as gender, race, and occupational position; (2) states of the characteristic such as male-female, white-black, and higher-lower occupational positions, which can partition the relevant population; (3) different status evaluations of these states relative to each other in terms of honor, prestige, and general social worth; and (4) high and low conceptions of the generalized capacities of the individuals who possess these different states, where these high and low conceptions are consistent with the status evaluation of the states. Thus gender may be a diffuse status characteristic for a population at a given time if the members of that population hold differential status evaluations for male and female, with, say, males being more highly esteemed, honored, and in general more socially valued than women, and with the members of the population commonly assuming that men are in general superior and more capable than women on a wide (and typically unspecified) range of valued tasks and activities. In this article we shall be concerned with developing a theory that describes the social construction of diffuse status characteristics.3

2 Other extensions of the core theory include the extension to open interaction situations, the extension to integrate source theory, and the extension to integrate status cue effects with status characteristics theory (Fis¸ek, Berger, and Norman 1991, 1995, 2005; Webster and Sobieszek 1974).

3 Status characteristic theories have been used to describe status organizing processes that involve, among other concrete status distinctions, differences in race (Cohen and Roper 1972; Brezina and Winder 2003); differences in gender (Lockheed and Hall 1976; Ridgeway and Diekema 1992; Wagner and Berger 1998); differences in ethnic identities, including Anglo vs. Mexican-American (Rosenholtz and Cohen 1985), Sephardic vs. Askenazi Jews (Cohen and Sharan 1980), and Anglo vs. Greek-Australian (Riches and Foddy 1989); differences in military status (Berger, Cohen, and Zelditch 1972); differences in educational attainment (Zelditch, Lauderdale, and Stublarec 1980; Markovsky, Smith, and Berger 1984); differences in occupational positions and sexual orientation (Webster, Hysom, and Fullmer 1998); and differences in physical attractiveness (Webster and Driskell 1983; Jackson, Hunter, and Hodge 1995).

The Status Construction Theory: An Overview The theory of status construction was originally developed by Cecilia Ridgeway to describe a process by which an initially nonvalued nominal characteristic acquires status beliefs and becomes a status characteristic (Ridgeway 1991). An example of a nonvalued nominal characteristic is one used by Ridgeway and her associates in their experimental research: the preference for Paul Klee over Wassily Kandinsky versus the preference for Kandinsky over Klee, as artists. Briefly, Ridgeway reasoned that if individuals who possessed the different states of a nonvalued characteristic, N, also were discriminated by their control of resources such as high and low levels of rewards, the differences in rewards would result in congruent high and low differences in their power and prestige positions. High and low assessments of the task performances of these individuals would then correspond with their differences in superordinate and subordinate power and prestige behaviors. She further reasoned that if individuals were exposed to multiple instances of these “double dissimilar situations” that were consistent (the same states of the characteristic, N, associated with same high or low level of rewards), a point could be reached where the superior-inferior performance assessments would come to be associated with the states of the neutral characteristic the individuals possessed. If this occurred the states of the initially neutral characteristic, N, would acquire status value, and through a process of diffusion (described in some detail), would become a status characteristic for a given population.

Ridgeway’s formulation has been further developed and her arguments tested in a series of cumulative experiments (Ridgeway et al. 1998; Ridge-way and Erickson 2000). In addition, her theory has been elaborated by her and others in a set of theoretical papers (Ridgeway 1997, 2000; Webster and Hysom 1998; Berger et al. 2002). Our theory is formulated within the framework of this important body of research.

Our principal concern in this article is with the core process of status construction. Following Ridgeway and others, we will separate the treatment of the core process of status construction from the process that deals with the diffusion of a constructed status characteristic through a given population. (For relevant papers on the issue of diffusion of a constructed status characteristic, see, in addition to Ridgeway’s original paper, Ridge-way and Balkwell [1997] and Mark, Smith-Lovin, and Ridgeway [2000].)

A Status Value Approach: An Overview

A common feature of Ridgeway’s approach and of that found in subsequent modifications and elaborations of her work by Ridgeway and others (Webster and Hysom 1998) is the focus on how differentiated status beliefs come to be attached to the states of an initially nonvalued characteristic through a process involving the possession of differential resources. In contrast, the focus of the approach to be developed here is on describing how an initially nonvalued characteristic can acquire status value and performance expectations as a result of its association with status characteristics and other status elements that already have status value and associated performance components. We also shall argue that when an initially nonvalued characteristic, say, N, does acquire status value, it becomes connected to generalized performance expectations. Further, as the initially nonvalued characteristic, N, builds up status value through associations with valued status elements, the connections between the states of the characteristic and those of performance expectations become stronger until they approach a maximum strength. Thus as the characteristic, N, accumulates status value it becomes increasingly effective in organizing the status behaviors of individuals until it reaches a maximum effectiveness. But we claim that more is required for such a characteristic N to become a status characteristic. We believe that the characteristic N must become an object in the public domain, that it must be externalized, and that it must become part of social reality. One way by which these changes can be achieved is through a process of social validation. This involves enacting, and consensually supporting, the meanings and behaviors implied by the status characteristic.

We summarize some of the major differences in these two approaches. To begin with, the Ridgeway et al. (1998) formulation argues that the fact that N(a)s and N(b)s control, say, high and low resources (e.g., rewards), respectively, leads to N(a)s occupying higher positions than N(b)s in the group’s interaction hierarchy. Second, it argues that the higher an individual’s position on the group’s interaction hierarchy, the higher the evaluation of the performances of that individual. Third, it argues that if such situations are repeated and consistent, a point can be reached where these high and low performance evaluations come to be attributed to the states of the N characteristic that an individual possesses. The key mechanism is the group’s interaction hierarchy. It is out of the evaluation of assertive (proactive) and deferential (reactive) performances of individuals in high and low positions, respectively, of the group’s interaction hierarchy that performance beliefs emerge which come to be attributed by actors to the states of N. On the other hand, in the formulation we present here, the process of status creation is initiated by the association of an initially nonvalued characteristic with already valued status elements such as existing diffuse and specific status characteristics. As a result of a spread of status value process, the states of the characteristic acquire differential status evaluations. Second, we argue that as the acquisition of status value occurs, generalized performance expectations emerge that become connected to the states of the initially nonvalued characteristic. Third, we argue that once these generalized performance expectations are maximally connected to the states of the newly evaluated characteristic, the confirmation of these expectations through a social validation process creates the likelihood that this characteristic becomes a stable diffuse status characteristic. The key mechanism is a process by which the status value of associated valued status elements spreads to the states of N, and as this occurs, differential generalized performance expectations are generated from the performance components of these valued status elements. The core theoretical processes involved in these formulations are schematically represented in figure 1.

It is to be noted that we do not conceive of these two formulations as describing conflicting processes. However, because they involve different core processes, they are likely to be applicable to different situations. That is, depending upon the specific conditions and the nature of any particular application, one or the other of these theories may be more appropriate to employ. Assuming this to be the case, our formulation enables us to expand the domain of problem areas to which status emergence theories can be applied (see below on our applications).

Our task now is to develop a formal theory of the construction of status characteristics that embodies these ideas on the acquisition of status value by associations and on social validation processes. Below, we shall review some of the concepts and principles from the graph version of the status characteristics theory that we need in our work. Then, we introduce the new concepts and assumptions that are used to describe this status construction process. Next, we examine some of the consequences of our new formulation. Finally, we briefly consider some applications of the theory and review and assess some of the implications of this research.

GRAPH FORMULATION OF STATUS THEORY: SOME BASIC CONCEPTS

In this section we shall describe just those basic concepts from the graph formulation of the status characteristics theory (Berger et al. 1977) that we need to develop our status value formulation. Since the status value formulation builds on the graph formulation of the status characteristics and the reward expectation states theories, we present the concepts and assumptions of those theories in appendix A.

The status characteristic and the reward expectations theories describe how actors use status information to form expectation states. They describe how status characteristics become admitted as usable items of in

Fig. 1.—Core theoretical processes

formation in the situation (salience), how they become connected with task and reward outcome states (burden of proof and activation of referential structures), and how the actors’ immediate situation changes with the admission of new actors, new status distinctions, and new tasks (sequencing).

We are concerned with representing a situation where a number of actors are collectively oriented to solving a task or a sequence of distinct tasks where each task has the valued outcomes of success and failure. These outcomes, represented by T(�) and T(�), are points in our graph, as are the states of a performance characteristic, C(∗ �) and C(∗ �), which, respectively, are instrumental to the success and failure outcomes of the group’s immediate task.

Our situation contains actors, p, o , o , ..., o , who possess states of

12 n

status characteristics that are either (a) initially connected to task outcomes by relevance relations, or who possess, say, diffuse status characteristics that (b) become connected through processes described by the status characteristics or the reward expectations theories. In figure 2 we present graph representations of two examples of these types of situations.

In the top part of figure 2, p possesses the high state, C( ∗ �), and o the low state, C( ∗ �), of a specific performance characteristic. The states of this characteristic are instrumental to outcomes of success, T(�), and failure, T(�), on the group task. This is an example of a situation where the actors are initially connected to task outcomes.

In the bottom part of figure 2, p possesses the more highly evaluated state, D(�), of a diffuse status characteristic, and o the less highly evaluated state, D(�), of that characteristic. The diffuse status characteristic has become salient, and high and low states of generalized expectations, G(�) and G(�), have come to connect the states of the status characteristic with the task outcome states by the action of the burden-of-proof process.

In reading these diagrams two things should be noted: (a) oppositely evaluated states that are possessed by the actors are separated from each other by a dimensionality relation which carries a negative sign, and (b) all other relations in the diagram (possession and relevance) have positive signs.

We shall call all paths starting from an actor and connected to a task outcome state actor paths of relevance. The length of any such path is simply the number of relations in the path. The sign of any such path is the product of the signs of the relations on the path times the sign of the outcome state to which the path is connected. Thus in the top part of figure 2, p has two positive paths of lengths 2 and 3, and o has two negative paths of lengths 2 and 3. In the bottom part of figure 2, p has two positive paths of lengths 4 and 5, and o has two negative relations of lengths 4 and 5.

Fig. 2.—Simple situational structures. Top: p possesses the high state, and o posseses the low state of a performance characteristic. Bottom: p posseses the high state, and o possesses the low state of a diffuse status characteristic not initially relevant to the task.

Paths of different lengths contribute different amounts to the expectations of an actor—specifically, the longer the path connecting the actor to an outcome state, the weaker its contribution to his performance expectations. To capture this idea the theory assumes that the strength of a path is given by a function, f(i), of its length, i. This function is an inverse function; that is, the longer the path, the less its strength. Paths can take on values in the interval (0, 1). The method for computing these values is given in appendix A.

In graphs that represent status situations in which differential rewards are distributed, there are additional points representing high and low reward levels which, respectively, are relevant to positively and negatively evaluated goal objects (or rewards). Our notion of actor paths of relevance with the concepts of length, sign, and strength of such paths that we previously developed also apply to situations that involve differential rewards where paths start from actors and can be connected to goal object outcomes.

In any given situation actors may be confronted with multiple salient status characteristics, with additional status information specific to the actors, and with information on behaviors that have occurred in their immediate situation. Such information generates multiple actor paths of relevance to outcome states. We assume that actors combine these paths in forming their aggregated expectation states in the immediate situation via a process we call the principle of organized subsets. The paths are combined within like-signed subsets according to the function

f(i ∪ j) p f(i) � f( j) � f(i) f( j)

and given the sign of the paths in the subset. The values of the two subsets are algebraically summed to yield the expectations for the actor. Expectations for actors can be combined in different ways to yield different expectation indices to predict particular kinds of behaviors. For example, the expectation advantage, which is the difference between the expectations for two actors, predicts acceptance or rejection of influence between the actors, and the expectation standing, which is an actor’s share of the total expectations in the situation, predicts the actor’s rate of participation in a discussion group.

CONCEPTS AND ASSUMPTIONS OF STATUS VALUE THEORY We now introduce a new type of path of relevance that we shall call a characteristic path of relevance. A characteristic path of relevance starts with the state of a characteristic that is connected to an actor who in turn is connected to the states of possessed evaluated status elements, for example, states of status characteristics or states of task abilities. Depending upon the situation, these paths are either initially connected to task and reward outcomes or come to be connected by the processes described in the status characteristics or reward expectation states theory. Our immediate concern is with characteristic paths of relevance that originate with states of an initially nonvalued characteristic. Figure 3 displays a representation of characteristic paths of relevance that start from states of N and connect to actors possessing the discriminating states of a diffuse status characteristic that has become relevant to task outcomes by the burden-of-proof process.

We shall directly apply the concepts that we have previously developed for the sign, the length, and the strength of actor paths of relevance to characteristic paths of relevance. Thus in figure 3, for example, there are two positive paths of lengths 5 and 6 starting from N(a) and two negative paths of lengths 5 and 6 starting from N(b) connecting N to the task outcomes. There are also four positive paths of lengths 4, 5, 6, and 7 starting from N(a), and four negative paths of the same lengths starting from N(b) connecting N to the reward outcomes. As is true with possessed valued status elements, we assume that the states of an initially nonvalued

Fig. 3.—Male with preference for Klee and female with preference for Kandinsky work together to prepare a scenario for an advertising TV clip. Rewards to be given on completion of the task.

characteristic become salient if they are a basis of discrimination or are directly connected to the task outcome states in the situation.

We now conceive of a process by which the states of N acquire status value because of their association with the valued states of status elements possessed by the actors in the situation.4 By the status value of charac

4 While we focus on association relations in this presentation, our formulation can be

teristic N, we refer to the relatively positive or negative or high-low evaluations of states of N in terms of honor, esteem, prestige, and general social worthiness. Let us for the moment fix on one state, say N(a), and ask what combination of paths will increase the positive status value of this state while simultaneously increasing the negative status value of the contrasting state, N(b). We shall say that all such paths are paths of positive significance and argue that paths of positive significance are paths which

  1. are positive paths connecting N(a) to task and reward outcome states, or
  2. are negative paths connecting N(b) to task and reward outcome states.

We now may ask what paths will increase the negative status value of N(a) and increase the positive status value of N(b). We shall say that with respect to N(a), these are paths of negative status significance, and we argue that paths of negative significance are paths which

  1. are positive paths connecting N(b) to task and reward outcome states, and
  2. are negative paths connecting N(a) to task and reward outcome states.

We now assume that characteristic paths of relevance will be combined within subsets of similar significance, subject to an attenuation effect, and that the strength of these subsets will be algebraically summed to determine the status value acquired by the nonvalued characteristic through association.5 These ideas are formally stated in the following assumption:

Assumption.—Formation of aggregated status value association.

Assume that states of an initially nonvalued discriminating characteristic are connected to outcome states by a set of paths of positive significance of strengths f(i),..., f(n) and a set of paths of negative significance of strengths f(i), ..., f(n). These paths will first be combined within

applied in a straightforward fashion to other connections between status elements, such as when the states of an initially nonvalued characteristic or goal object (see below) is relevant to a valued status element.

5 The general form of the combining principle we use here is similar to that introduced in Berger et al. (1977) to describe the way actors aggregate established status information. It has been used effectively in accounting for relevant empirical research and in developing theoretical extensions of the core status characteristics theory.

subsets of similar significance to yield a positive association value, n �, and a negative association value, n �, via the following functions:

n � p [1 � (1 � f(i)) (1 � f(n))],

n p �[1 � (1 � f(i )) (1 � f(n ))].

The aggregated status value acquired by an initially nonvalued characteristic through association is given by

n p n �� n � .

As the status value association of the initially nonvalued characteristic, N, increases, a differential evaluation of its states emerges. As this differential evaluation emerges, the states of high and low generalized performance expectations come to be connected to the states of N in a consistent manner. As previously observed, these states of generalized expectations represent relatively greater and lesser performance capacities on a broad and unspecified range of tasks that individuals who hold different states of N are expected to possess given simply that they possess these different states. We assume that these performance expectations are generated from the performance components associated with valued status elements such as the generalized expectations associated with diffuse status characteristics. Thus, as the discriminating characteristic, N, acquires status value by its association with already valued status elements in the situation, it also acquires generalized performance expectations. Furthermore, we assume that the lines connecting the differentially evaluated states of N, N(�/�), to high and low states of generalized performance expectations, G(�) and G(�), are of variable length and inversely related to n, the strength of the status value association of N.6 Therefore, as the value of n increases for a given N, the length of the lines connecting its states with states of high and low generalized performance expectations decrease. They can decrease until they approach a line of length 1. A line of length 1, it is important to observe, is exactly the length of those lines connecting the states of generalized expectations with the states of an already established diffuse status characteristic (see bottom half of fig. 2). These ideas are presented in the following assumption:

Assumption.—Evaluated states and generalized expectations.

Assume that the states of an initially nonvalued discriminating characteristic N have become differentially evaluated. Then these states, N(�/�), will become connected by lines of length l, in a consistent manner

6 For a related theoretical problem that has involved introducing variable-length lines to describe the strength of the connection of elements in a status graph, see Fis¸ek et al. (1995).

with the states of generalized expectations, G(�/�). These lines will be of variable length, and their length is given by a function,

a

l p 1/n .

The effect of a in the above expression is to increase the rate at which l goes to one for a ! 1, and to decrease that rate for a 1 1, given n ! 1. The parameter a is necessary because the length of the line connecting N(�/�) to G(�/�) may depend on situational factors other than association, such as degree of task orientation or relations of sentiment among the actors. The a parameter can account for the effect of such factors.

We assume that if the differential evaluation of the states of N has occurred, the operation of N in a task situation is governed by the principles of the status characteristic theory: If, in a given situation, it is a basis of discrimination, then it will become salient. If it is salient and not initially connected to outcome states, then it will become outcome connected through the burden-of-proof process. If it operates in a situation where established status elements exist, it will be aggregated along with these elements in the formation of aggregated expectation states via the principle of organized subsets (see app. A).

By the spread of status value processes we have described above, it is possible for an initially nonvalued characteristic, N, to acquire a maximum status value. However, we argue that more is required for such a characteristic to become a diffuse status characteristic. We believe that this newly evaluated characteristic, N, and its behavioral implications must be established as an object in the public domain, that it must be externalized through the behavior of others, and that it must be defined as being real through a demonstration of social consensus. One of the ways (but surely not the only one) by which this can occur is through a process of social validation (Berger et al. 2002). Given, for example, that an actor in the group behaves in accord with the performance expectations of the newly evaluated characteristic, N, and that this behavior is supported or affirmed by others, we say that the characteristic, N, has been socially validated. An actor is said to behave in accord with the performance expectations of the characteristic if she or he behaves in a proactive and assertive manner when possessing the positively evaluated state of the characteristic, and in a reactive and deferential manner when possessing the negatively evaluated state of the characteristic. There are at least three important consequences of the social validation process. The validation process confirms the performance expectations of the newly evaluated characteristic, N;it translates these performance expectations into publicly observable behaviors that define the role of the actor, the reactor, and the bystanding other; and it demonstrates that there is a consensus on the existence of the newly evaluated characteristic within the immediate group.

Validation may be strong (explicit) or weak (implicit). The behavior of one actor is strongly validated by a second if the second actor’s behavior is similar to, supportive of, or overtly confirms that of the first. The behavior of one actor is weakly validated by a second if the second does not engage in behavior that is inconsistent or contradicts that of the first. We shall say that the behavior of an actor is validated by a specific other if the specific other strongly validates the actor’s behavior while the remaining members of the group (if any) weakly validate that behavior.7

We now argue that if an actor in a group acts in accord with the performance expectations of a characteristic, N, that has acquired a maximum status value association, and if that behavior is socially validated by a specific other, the probability exists that this characteristic becomes a diffuse status characteristic for the individuals involved. In addition, validation by multiple specific others will increase that probability. These ideas are stated in the following assumption:

Assumption.—Construction of a diffuse status characteristic.

Given a characteristic, N, whose status value association, n, comes within epsilon of one. Assume an actor in the group behaves in accord with the performance expectations of this characteristic. If the actor’s behavior is strongly validated by a specific other, then there is a probability that this characteristic becomes a diffuse status characteristic for the actors involved. The greater the number of specific others validating the actor’s behavior, the greater this probability.

Given that a characteristic N has become a diffuse status characteristic for a given population to which it is applicable in a given situation, what factors can account for its stability? We believe that there are at least three factors that are extremely important: the status organizing process, the reverse process, and the maintenance of the generating valued set.

Status organizing process.—If N has become a diffuse status characteristic, the core status characteristics and expectation states theory describes it impact on behavior. According to that theory, if N becomes salient it will be used in determining superordinate and subordinate power and prestige positions that actors come to occupy in the group. These

7 We have described the validation sequence, above, as being initiated by the actor possessing a state of N and being responded to by other. However, other concrete sequences may be instances of validating, e.g., action initiated by other and responded to by the actor, or action initiated by one other and responded to by a second other, provided that these actions confirm the expectations in N and demonstrate consensus on those expectations to the actors in the situation. In addition, it should be noted that validation may be experienced from the perspective of the interacting actor and other, as well as from the perspective of a bystanding other.

positions in turn are expected to be consistent with actors’ status states on N. We can also expect to find that the evaluations of actors’ performances in a given situation will be based on their power and prestige positions. If this is so, these evaluations will tend to be consistent with the generalized performance expectations embodied in N and therefore will operate to maintain N as a diffuse status characteristic (Ridgeway 1991; Berger et al. 2002).

Reverse process.—Aside from the outcome of a normal status organizing process as described above, the stability of N as a diffuse status characteristic can be also enhanced in situations where differential rewards are allocated. Theoretical arguments claim (Berger et al. 1985), and previous research has demonstrated (Cook 1975; Harrod 1980; Bierhoff, Buck, and Klein 1986; Stewart and Moore 1992), that by what is referred to as the “reverse process” (Berger, Zelditch et al. 1972), the allocation of high and low rewards will generate, respectively, high and low performance expectations. Thus in situations where high and low rewards are allocated consistent with the high and low evaluated states of N, a fairly common occurrence, the allocation of such rewards is expected to contribute to the stability of N as a status characteristic.

Maintenance of valued set.—In addition to the normal operation of the status organizing process and the operation of the reverse process, we argue that the maintenance of the valued set that is involved in the generation of the status value of N is important to maintaining the stability of N as a status characteristic. If the elements of the set are modified or eliminated and are not replaced by an equivalent set of elements, then the status value of N will be accordingly modified, as will also the strength of its association with the states of generalized performance expectations. Furthermore, we suggest that there may be an important difference in the relation of these three factors to the stability of N. While the normal status organizing process and the reverse process may operate as sufficient conditions for the stability of N, the maintenance of the valued set from which the status evaluation of N is generated may operate as a necessary condition for the stability of N as a diffuse status characteristic.

THEORETICAL CONSEQUENCES

Our formal theory of status construction consists of those concepts and assumptions we have just developed conjoined with those from the theories of status characteristics, reward expectations, and the transfer of expectations. From these arguments we are able to derive assertions about general conditions that affect the acquisition of status value. In addition, we can also make predictions about the effect of an initially nonvalued characteristic, N, after it has acquired some status value in different specific status situations.

Our concern in this section is with how different types of status conditions affect the process by which an initially nonvalued discriminating characteristic acquires status value. There is no attempt, of course, to be exhaustive of all that can be said on the basis of our formulation. Rather, we concentrate on results that we believe are substantively informative and that are important for empirical tests.

For the results that follow we assume that there are a number of actors, p, o1, o2, ..., on, who are interacting in a collective and valued task situation, who accept the evaluations and expectations embodied in status elements (diffuse and specific status characteristic and goal objects) that become salient, and who assume (unless and until they learn otherwise) that there is consensus in the group on these evaluations and expectations. Further, in some situations, the allocation of differential rewards may be part of the initial working conditions. In such situations, in addition to forming task expectations, our theory also describes the processes by which actors form reward expectations (see app. A). A situation in which these conditions obtain is designated as situation S.

Before proceeding we introduce some terms that we use in formulating and proving these assertions. A discriminating status element is a status characteristic, diffuse or specific, and/or a goal object whose differentially evaluated states are possessed by interactants in the given situation S.A set of status elements is consistently assigned in the situation if, in the graph representing S, all paths joining interactants with outcome states that contain the status elements in the set have the same sign. A status element is normal, if in the graph representing S, there is no actor for whom there are both positive and negative paths to outcome states containing this element. We shall assume in what follows that all status elements that are being considered are normal.

For convenience in exposition we shall group our results into four sets: basic conditions of status value acquisition, expectation advantages and status value acquisition, status structures and status value acquisition, and task and reward outcomes and status value acquisition. For proofs of these results, see appendix B.

Basic Conditions of Status Value Acquisition Given our theory, can we formulate basic and general conditions under which an initially nonvalued discriminating characteristic will acquire status value? Our theory in fact enables us to stipulate a set of such conditions.

Imagine a situation S, where there are at least two actors, p and o, who possess different states of an initially nonvalued characteristic. In addition, p and o possess the oppositely evaluated states of any number of discriminating status elements, and they perform a task together. Further, one of these actors, p or o, has a task and/or reward expectation advantage over the other. We predict that under such conditions the initially non-valued characteristic will acquire status value. For example, a situation in which p possesses the N(a) state of N (say, prefers Klee over Kandinsky) and o the N(b) state (preferring Kandinsky over Klee), and in which p is a black male professional and o is a white female secretary (and race, gender, and occupation are equally weighted), comes within our general conditions. In this situation p will have a task expectation advantage over o, and we predict that the initially nonvalued states of characteristic N will acquire status value. In theorem 1, we state this basic result.

Theorem 1.—Basic conditions of status value acquisition.

Assume that p and o are interacting in situation S such that: (1) p and

o possess the different states of a nonvalued characteristic, N(a) and N(b), respectively; (2) p and o are discriminated by normal status elements; and

(3) p has a task and/or reward expectation advantage over o; then the initially nonvalued characteristic, N, will acquire status value.

In the following theorems we assume that the actors are in an S situation and that the basic conditions of value acquisition as defined by theorem 1 are given.

Expectation Advantages and Status Value Acquisition Given that we can describe basic and general conditions under which an initially nonvalued characteristic acquires status value, are there general conditions under which we would expect to find an increase or decrease in the acquired status value of a nonvalued characteristic? To answer this question we build on the basic conditions of status value acquisition given in theorem 1 and reason that if any new discriminating status elements become salient in this situation that increase or decrease p’s task and/or reward expectation advantage over o, this change will result in an increase or decrease, respectively, of the status value association of the characteristic. If the black male professional and the white female secretary learn that he has greater competence on the task then she does, his expectation advantage over her will increase, and the status value association of artist preference will also increase. This result is stated in theorem 2.

Theorem 2.—Expectation advantage and status value acquisition.

If new discriminating status elements that increase or decrease p’s task and/or reward expectation advantage over o become salient, then the status value acquired by the nonvalued characteristic, N, will, respectively, increase or decrease.

Status Structures and Acquisition of Status Value The configuration of the status structure that exists in a given situation has a major impact on the process by which a nonvalued characteristic acquires status valuation. Given the basic conditions for the acquisition of status value, the more monolithic the status structure that exists in a situation at a given time, the greater the acquisition of status value. A monolithic structure is one in which the status distinctions are consistent, are highly relevant to task and goal object outcomes, are comprehensive, and reflect a high level of uniformity. We consider each of these factors separately.

Consistency.—Status structures may differ in the degree of consistency that exists among the different status distinctions in the structure. In a fully consistent structure all actors possess the same status level on each of the different status distinctions that are salient in the situation. In an inconsistent structure actors may hold high positions on some status characteristic while holding low positions on other characteristics. The important consideration is that in consistent structures, status characteristics are providing actors with mutually supporting information on how to evaluate and what to expect of the different members in the group. In inconsistent structures status characteristics are providing actors with contradictory information on how to evaluate and what to expect from the different members of the group. Therefore, given our basic conditions for the acquisition of status value, we would expect to find that the greater the degree of status consistency of a structure the greater the acquisition of status value by an initially nonvalued characteristic. What does this mean in terms of our basic example? If in our example case, the male professional had been white and the female secretary had been black, the discriminating characteristics would have been more consistent, and his expectation advantage over her would have been greater together with the status value association of artist preference. Our general result on the effect of consistency is given in theorem 3.

Theorem 3.—Consistency of status elements and status value acquisition.

Assume that p and o are discriminated by a fixed number of status elements equally relevant to task outcomes. The greater the consistency of these status elements, the greater the status value acquired by the nonvalued characteristic, N.

Relevance.—Status characteristics in status structures may differ in their relevance to the group’s goal states. In some status structures, existing status distinctions are closely tied to the group’s task goals. In other structures, status distinctions have either no initial connection or have an extended connection to these goals. The degree of relevance of a status characteristic depends on the nature of the characteristic, the nature of the task, and the actors’ beliefs about the characteristic. In this context, consider the common belief in our culture that associates mechanical ability and gender. As a consequence of this belief, gender typically is a directly relevant status characteristic in a situation involving a mechanical task. Given other situations, gender may have no initial connection to the task goal, but may become connected to the task through the burden-ofproof process (see fig. 3).

What is important here is the theoretical argument that the greater the degree of relevance of a status characteristic to a task goal, the stronger are the expectations provided by that characteristic which connects an actor to the task. As a consequence, what we expect to find, given our basic conditions for the acquisition of status value, is that differences in the relevancies between any two otherwise similar status structures will produce corresponding differences in the processes by which the non-valued characteristic N acquires status value. What does this mean in terms of our gender example? If a male and female are discriminated by artist preferences, and they are working on a mechanical task, his expectation advantage over her will be greater than it would be if they are working on a task in which gender is not initially connected to the task. As a consequence, the status value acquired by type of artist preference will be greater in the first situation as compared to the second situation. Our general arguments concerning the effect of relevance are stated in theorem 4.

Theorem 4.—The relevance of status elements and status value acquisition.

Assume that p and o are consistently discriminated by a fixed number of status elements that are equally relevant to task outcomes. The greater the relevance of the status elements to task outcomes, the greater the status value acquired by the nonvalued characteristic, N.

Comprehensiveness.—Given a status structure consisting of a set of discriminating and consistently allocated status characteristics, the introduction of an additional discriminating characteristic consistent with the initial set increases the comprehensiveness of the structure. Each additional status characteristic reinforces and increases the impact of the initial set of characteristics on the status behavior in the situation. Therefore, given our basic conditions for the acquisition of status value, we would expect to find that the more comprehensive the status structure, the greater the acquisition of status value for an initially nonvalued characteristic. To see what this means consider the consistent version of our basic example, where p and o are discriminated on artist preferences, and p is a white male professional and o is a black female secretary. If we now learn that p is a good athlete and o is a poor athlete, the number of status elements discriminating them will be increased. The result is that p’s expectation advantage over o will be increased as will the status value acquired by type of artist preferences.

The general process we have been describing is subject to an attenuation effect. The more status characteristics in the initial set, the less the incremental change that results with each additional characteristic. These ideas are given in theorem 5.

Theorem 5.—The number of status elements and status value acquisition.

Assume that p and o are consistently discriminated by a number of status elements equally relevant to the task outcomes. The greater the number of these status elements, the greater the status value acquired by the nonvalued characteristic, N. However, the marginal contribution of each element will be less as the number of characteristics increases.

Uniformity.—The number of actors in a group who possess oppositely defined states of an initially nonvalued characteristic and discriminating states of valued status elements can affect the acquisition of status value. This can come about in the following way. Given that actors who possess the different states of an initially nonvalued characteristic also possess a fixed number of consistent discriminating status characteristics, then the greater the number of actors involved in the situation, the greater the status value association of the characteristic N. In the simplest case, if actors who are discriminated on the possession of N(a) and N(b) are uniformly discriminated on gender, that is, all males possess one state of N and all females the second state of N, then the greater the number of males and females involved, the greater the status value acquisition of

N. These ideas are stated in theorem 6. Theorem 6.—Number of actors and status value acquisition. Assume that p and o2 through oN are actors such that:

  1. p and o2 through ok (k ! n) possess the N(a) state of a nonvalued characteristic N, and ok�1 through on possess the N(b) state;
  2. p and o2 through ok and ok�1 through on are consistently discriminated by a fixed number of status elements of equal relevance; and
  3. p and o2 through ok have task and/or reward expectation advantages over ok�1 through on.

The greater the number, n, actors in this situation, the greater the status value acquired by the nonvalued characteristic, N.

Outcomes and the Acquisition of Status Value

In this section we shall deal with status value acquisition effects that occur in situations in which actors work on a sequence of successive tasks.

We are particularly concerned with how the assignment of task success or task failure and/or the allocation of differentially evaluated goal objects (or rewards) affect the status value acquisition process. The status characteristics theory is formulated to deal with such task sequence situations (Berger et al. 1989).

Before turning to these theorems we must first attend to some preliminary matters. It can be shown that when sequences of successive tasks occur, expectations that are formed on an initial task can transfer to the succeeding task (Markovsky et al. 1984; Berger et al. 1989). It can also be shown that the status value acquired by an initially nonvalued discriminating characteristic can increase until it reaches a stable limiting value simply as a result of the fact that actors are working on successive tasks. In our next two theorems we restrict ourselves to situations in which the discriminating status elements possessed by the actors are not initially connected to outcome states, and where successive tasks are not dissociated or inversely related to each other.8

There are many factors that can affect actors’ expectations when they move through a successive sequence of tasks. These include the introduction of new tasks, the introduction of new information on the skills and abilities of actors already in the situation, and the introduction of new actors with the new salient status distinctions that they might possess. Among the factors that have a major impact on actors’ expectations are evaluations of their overall performances in terms of task success and task failure. Such evaluations, which may or may not be based on explicit performance standards, may come from external authorities, or they may be the result of consensual assessments occurring within the group. Be that as it may, we assume that these evaluations involve the assignment of task success and task failure outcome states to specific actors. Given our basic conditions for the acquisition of status value, such assignments, occurring at the end of one task episode and when consistent, will increase the status value acquired by the nonvalued discriminating characteristic on the succeeding task. An assignment is consistent if the actor with the expectation advantage is assigned task success, and that actor with the disadvantage is assigned task failure. These ideas are given in the following theorem.

Theorem 7.—Success/failure and status value acquisition.

Assume that (1) the status elements discriminating p and o are not

8 Two tasks are dissociated if, by cultural convention, the abilities involved in each are so defined that it is not possible to predict the level of one ability from information about the second. Two tasks are inversely related to each other if, by cultural definitions, high ability on one task is associated with low ability on the second, and low ability on one is associated with high ability on the other.

initially task relevant, and (2) that p and o interact on two successive tasks that are not dissociated or inversely related to each other. If task outcomes are consistently attained by p and o on the first task, then the status value acquired by the nonvalued characteristic, N, will increase on the second task.

In what follows, the antecedent conditions stated in 1 and 2 in this theorem are referred to as the basic conditions of transfer of expectations.

In situations where differential rewards are to be distributed, actors form expectations for goal objects (or rewards). In such situations, as is true in the case of the overall evaluations of performances, the allocation of goal objects may have a major effect in changing actors’ expectations as they move from one task setting to another. Again we are interested in situations where the allocation, which involves differentially valued goal objects, occurs at the end of one task episode, and where our basic conditions for the acquisition of status value obtain. Given such conditions, we argue that if differentially valued goal objects are allocated to specific actors in a consistent manner on a given task, then the status value of the initially nonvalued discriminating characteristic possessed by these actors will increase on their succeeding task. Goal objects are consistently allocated if the actor with the expectation advantage receives the more highly valued goal object, and the one with the expectation disadvantage receives the less highly valued goal object. Thus, if the white male professional who prefers Klee works with the black female secretary who prefers Kandinsky on a “contrast sensitivity” task, at the end of which the male receives the highly valued reward while the female receives the less valued reward, and they start to work together on a “meaning insight” task, the status value association of artist preference will increase substantially. The general ideas are presented in our final theorem.

Theorem 8.—Allocation of rewards and status value acquisition.

Assume that the basic conditions of transfer of expectations obtain. If goal objects are consistently allocated to p and o on the first task, then the status value acquired by the nonvalued characteristic, N, will increase on the second task.

As a set, all of the theorems presented above describe social conditions under which there is greater and lesser likelihood that a diffuse status characteristic will be created. Since these results are new in the study of status creation processes, the task ahead will be to subject them to empirical tests.

APPLICATIONS We can apply our theory to understanding some of the important and puzzling issues connected with the maintenance of established status characteristics. For example, since a characteristic can acquire status value and generalized expectations as a result of its association with a set of discriminating valued status elements, what do we expect to occur if the initial set of valued status elements no longer exists? Our theory predicts that in this case, the differences in the status evaluations of states of the characteristic will be reduced (if not disappear) as will be the differences in performance expectations associated with these states. If this is the case, how can we explain the situation where the initial set of valued and discriminating status elements is no longer associated with the states of a characteristic, but where these states are still differentially valued, and expectations of superiority and inferiority continue to exist? It seems reasonable to suggest that under these circumstances the initial set of valued status elements has been replaced by an equivalent set of discriminating and valued status elements. Thus, for example, there is little question that the association of the differentially valued states of freeman and slave with those of whites and blacks played a fundamental role in the emergence of race as a diffuse status characteristic in colonial American society (Durant and Knottnerus 1999; Ellis 2000; Wiencek 2003). But while the freeman-slave distinction no longer exists and therefore is no longer associated with the states of race, race continues to operate as a diffuse status characteristic. Our theory leads us to believe that an equivalency set probably exists. In all likelihood, among the most important elements in this set are different levels of educational attainment and different levels of occupational positions, with those associated with whites being generally more highly evaluated and more highly rewarded than those associated with blacks. It is reasonable to hypothesize that race may continue to be a diffuse status characteristic in our society as long as such status elements remain associated with its states. Thus our formulation identifies the importance of equivalency sets. It highlights the need to identify their elements and determine their specific role in maintaining the status evaluations and expectations of superiority and inferiority that continue to be associated with such established status characteristics as gender, race, and ethnic distinctions in our society.

Our theory may be useful in understanding some of the consequences of mass migration movements for intergroup relations. Assume that an immigrant group moves into a particular country and that the related social categories of “native population” group to “immigrant X” group come into existence.9 As has been true of most such groups in the south

9 While there may exist prior evaluations of these populations relative to each other,

to north and east to west migrations into Europe since World War II, the members of such an immigrant group may occupy lower occupational positions, earn considerably less, and possess lower educational levels than is generally true of individuals in the native population (Castles and Kosack 1985). Given these conditions, we expect the spread of status values to the social categories of immigrant X and native population, with the evaluations of the former tending to be negative while those of the latter tend to be relatively positive. Simultaneous with this process, according to our theory, high and low generalized performance expectations will become strongly connected, respectively, to the native population state and the immigrant X state. It is also important to note in describing these processes that the nature and extent of cultural, religious, and physical differences that exist between the native population and the immigrant group can play a crucial role in their outcome. Be that as it may, out of these conditions and the status value processes we have described, a diffuse status characteristic can be created that then gives rise to the problems of racism, which are manifested in prejudicial attitudes, discrimination, and political action (Pettigrew 1998).

In the situation described above, in-group/out-group biases, from the standpoint of the native population, are operating congruently with spread of status value processes in defining the immigrant X group. But assume the existence of an immigrant group Y, such as Chinese immigrants in Malaysia, whose members in general occupy or come to attain a highly advantaged position in the economic structure of the society (in terms of occupations, earnings, and education) relative to the indigenous population (Sowell 1996).10 In this case the differential evaluations based on spread of status value processes are working in opposition to those based on in-group/out-group biases. We would expect to find positive evaluations of this group by the native population as a result of status value processes as well as negative reactions stemming from the fact that they are an out-group, and from the fact that the native population is in a socially disadvantaged position. However, since status value processes and in-group/ out-group biases are operating congruently from the standpoint of immigrant group Y, we expect them to form relatively strong negative

we are assuming that new social categories of indigenous population–immigrant group

emerge when one population becomes an immigrant group to the second. 10 Sowell points out that in the beginning the Chinese were at the bottom of the occupational structure and subsequently rose economically. “Whereas more than half of all Chinese in 1911 were agricultural laborers or mining laborers, just twenty years later only 11 percent of the Chinese were in these two occupations” (Sowell 1996, p. 192). At the same time, it should be noted that by 1970, major disparities favoring the Chinese existed in the household incomes of the Chinese and Malays in Peninsular Malaysia, which, with some reductions, still held true in 1990 (Pan 1999, p. 181).

evaluations of the status worth of the native population. If we consider in this context, for example, the case of Chinese immigrants and Malays, we find that reports on the conceptions of these groups by each other, in general, have been consistent with these theoretical expectations (Vreeland et al. 1977).11 More generally, our theory may enable us to understand the processes and the conditions under which native population–immigrant group distinctions are transformed into diffuse status distinctions. In fact, this may be the principal social setting out of which ascriptive diffuse status characteristics are currently being created.

Nothing in our conception of a diffuse status characteristic requires that it be applicable to the population of an entire society as in the case of such status categories as race, gender, and age. The emergence and breakdown of such encompassing diffuse status characteristics may represent socially important but unusual events. However, the emergence, modification, and even breakdown of status categories that are applicable to more restricted contexts may in fact be much more common events.

The spread of status value theory may be applied to account for the development of status characteristics (including informal ones) within organizational and institutional contexts. It may be used, for example, to account for the emergence in universities of status categories that are based on students’ different fields of study. Thus, for example, the differences in the status evaluations and generalized performance expectations embodied in such categories as “techies” and “fuzzies” can be explained by the association of different fields of study with occupations which in our society differ markedly in prestige and rewards. Changes in this association between fields of study and occupations that differ in social prestige and rewards should produce changes in the evaluation of these student status categories.

This theory may also be used to account for differences in the status evaluations accorded to different regional settings. Thus, for example, the relatively high or low status evaluations accorded to different residential areas may be accounted for by the associated differences in these areas of residents who differ on educational or ethnic or racial status characteristics. From this standpoint, changes in the association of a residential area and the racial or ethnic or occupational composition of its residents can explain both the gains and losses in status that are so often found to occur in different residential areas.

11 See reports in Vreeland et al. (1977, p. 89) and Ness (1967, p. 46). See also Rabushka (1973) who reports the results of an opinion poll on race and politics of urban Malays and Chinese. It should be noted that these reports are principally for periods prior to the start of the major affirmative action program in the New Economic Policy introduced by the Malaysian government in 1970.

The spread of status value theory can also be used to describe the process by which the states of an initially nonvalued social object can become a goal object, that is, an exchange object with states that embody different levels of social worth. Shane Thye, in an important set of experiments (2000), has shown how poker chips of different colors can be made to acquire different levels of status value. In Thye’s experiments, different-colored poker chips are associated with the differentially evaluated states of diffuse and specific status characteristics, and by a spread of status value process, high and low evaluations are transferred from the status characteristics to these objects. Thye then shows that these different-colored poker chips are treated as having greater or lesser amounts of exchange value among actors who are interacting on a set of negotiating tasks in a network exchange situation (Thye 2000). The theory we have presented here can be applied to give a general account of this spread of status value process. In addition, our theory predicts that actors who possess the different states of this goal object (the different-colored poker chips) will also differ, in a status-consistent manner, in the generalized performance expectations that they hold. Recent work by Thye (2003) and Thye et al. (2005), in which they introduce the notion of performance expectations to predict an actor’s negotiating behavior, in fact, provides support for this theoretical derivation from our formulation. Finally we observe that by this application, the spread of status value theory provides a theoretical bridge for two programs of research that up to now have been pursued along independent lines: research on the social construction of status characteristics and research on the construction of status-valued social objects.

SUMMARY AND GLIMPSES BEYOND The idea of the spread of status value is an old one in sociology (Veblen 1899); however, there have been but few attempts to develop rigorous theory using this idea (Berger, Zelditch et al. 1972; Thye 2000). In this article we have presented a formal theory that embodies this idea to describe how an initially nonvalued discriminating characteristic can become a diffuse status characteristic. The assumptions of our theory have three major components.

First, they describe how the states of the discriminating characteristic can acquire differential evaluations in terms of honor, esteem, prestige, and general social worthiness. This can occur by the association of these states of the discriminating characteristic with established status elements—for example, diffuse and specific status characteristics—that already possess status value.

Second, our theory argues that when the discriminating characteristic acquires status value, states of generalized performance expectations come to be connected to the states of the discriminating characteristic in a consistent manner. Further, as the status value acquired by the discriminating characteristic approaches a maximum value, the connections of states of generalized performance expectations to states of the discriminating characteristic approach a maximum strength.

Third, given that the status value acquired by the discriminating characteristic has attained maximum value, then if the performance expectations of the characteristic are socially validated, the probability exists that the characteristic will become a diffuse status characteristic. By social validation, the behavioral meaning of the characteristic is confirmed and is shown to be a consensually accepted object of social reality.

We have also presented a set of theorems that are theoretical consequences of our formulation. These describe different types of conditions that affect the status acquisition process. Among the most important of these are conditions that describe the effects of different types of status structures and the effects of task success and failure, as well as the allocation of goal objects (rewards) on the acquisition process.12

Our assumptions and theorems allow us to construct empirical tests of the many consequences of our formulation. Further, since a constructed diffuse status characteristic, as conceptualized in this theory, has the same properties as a diffuse status characteristic as originally conceptualized in the core status characteristics theory (Berger et al. 1977), this also enables us to use the principles and consequences of the core theory and its theoretical extensions to construct rigorous empirical tests of the spread of status value formulation.13

Finally, as we have previously observed, we make no claim that there

12 While not strictly derivable, our theory may also enable us to formulate a strategy by which it is possible to break down a status characteristic once it is constructed. The strategy essentially entails reversing the status value process involved in construction and consists of two interventions. The first of these is to reduce the status evaluation of the characteristic, N, from a value equal to or close to one, to a value equal to or close to zero. This can be done by introducing a determinable number of inconsistent status elements that associate high status elements with the low state of N and low status elements with the high state of N. The second intervention is to confirm the equality in expectations produced by the first intervention through a social validation process that enacts this status equality in behavior. See also Ridgeway and Correll (2000).

13 In this context it is worth noting that aside from studies in the United States, in the past, expectation state processes have been studied in other cultures and countries. These include Israel (Yuchtman-Yarr and Semyonov 1979), Germany (Bierhoff et al. 1986), France (Lambert and Ehrlich 1980), Holland (Wilke, van Knippenberg, and Bruins 1986; De Gilder and Wilke 1990), Canada (Foschi and Buchan 1990), Australia (Foddy and Riches 2000), and Turkey (Fis¸ek and Hysom 2004).

is a unique process that can explain the construction of status categories. We believe that a number of different processes such as that represented by Ridgeway’s interaction-hierarchy approach or that represented by the spread of status value approach (or still other approaches involving general processes), singly or in combination, may be necessary to account for the emergence of status categories in different types of situations. Furthermore, we recognize that historically particular events may play important roles in the shaping of particular status distinctions. Nevertheless we do believe that if we can understand theoretically the general social processes by which status characteristics are constructed, we may also understand how such characteristics, with their invidious beliefs and status evaluations, can be modified and fundamentally changed. We think this is a theoretical challenge to which it is worth responding.

APPENDIX A

Core Theory and Extensions In this appendix we first give a full statement of the assumptions of the core theory of status characteristics and expectation states together with the auxiliary assumptions introduced by the reward expectations and the evolution of expectations extensions of the core theory. We then use the situational graph given in figure 3 and a further development of this graph given in figure A1 below to describe the applications of these assumptions. We also demonstrate the computation of expectation advantage of one actor over another and the status value association of an initially non-valued characteristic using the earlier formulations presented here together with the current developments presented in this paper.

Assumption.

  1. Given existing paths connecting an interactant to outcome states of the group task, the elements and the relations in these paths become salient in the task situation.
  2. Given status elements that provide a basis for discrimination between the interactants, the states of these characteristics become salient in the task situation.

Assumption.—Burden of proof.

Given that a salient status element possessed by an actor is not connected to a task outcome state, if the element is

  1. a diffuse status characteristic, then the associated general expectation state will be activated, and it will become relevant to the similarly valued state of the instrumental ability relevant to the task;
    1. a specific status characteristic, then its relevant task outcome state
    2. will be activated and will become relevant to the similarly evaluated state of abstract task ability, and the latter will become relevant to the similarly evaluated task outcome state;
  2. a behavior interchange pattern, then its relevant status typification states will be activated and will become relevant to similarly evaluated states of abstract task ability, and the latter will become relevant to similarly evaluated task outcome states.

Assumption.—Sequence of structure completion.

A given structure will be developed for the interactants through the processes of salience and burden of proof. If a noninteractant later becomes an interactant, or a new actor enters the situation, a new task is introduced, a new behavior interchange pattern comes into existence, or new imputations of status characteristics are made, then the structure will be further developed through the operation of the same processes. For any actor, those parts of the actor’s structure previously completed will remain while the actor is in the given situation.

Assumption.—Formation of aggregated expectation states.

Given that an actor x is connected to states of an outcome a(�) (task or reward) by sets of positive paths of strengths f(i),..., f(n) and negative paths of strengths f(i), ..., f(n). These paths will first be combined within like-signed subsets to yield a positive path value, ex a(�), and a negative path value, eax (�), via the following function:

a(�) …

ex p 1 � [1 � f(i)] [1 � f(n)],

a(�)

ex p �(1 � [1 � f(i)] … [1 � f(n )]).

The aggregated expectation state is then given by

eaa(�) � ea(�)

p e .

xx x

Assumption.—Basic expectation assumption.

Given that p has formed aggregated expectation states for self and other, p’s power and prestige position relative to o will be a direct continuous function of p’s expectation advantage over o.

Auxiliary Assumption.—Activation of referential structures.

Given status characteristics that are salient in situation S, if these characteristics are referentially associated with states of reward levels, relevance relations will come to be induced between states of the characteristics and similarly evaluated states of the reward levels in S.

Auxiliary Assumption.—Relevance of task outcome states.

Given any successive group tasks that are not dissociated or inversely related to each other. If on completion of the first task, the actor engages in the second task, then relevance relations will be established in a consistent manner between the outcome states of the two tasks.

Figure 3 gives the situational graph for a hypothetical situation—a male Klee fan and a female Kandinsky fan are writing a scenario together for a television advertising clip, and rewards are to be given for task performance. We now want to describe how this situational graph is determined by our formulation. First, any situational graph starts out with a minimal initial structure. The minimal structure consists of one point for each actor (at least two of them), and a task outcome structure which consists of the task outcome states, T(�) and T(�), standing for task success and failure, respectively, and the states of the instrumental characteristic (i.e., the ability necessary to perform the task), C∗(�) and C∗(�), standing for high and low ability states, respectively. The states of the instrumental characteristic are relevant to the similarly signed states of task outcomes. If rewards are to be given in the situation, the initial graph also includes the reward outcome structure which consists of the reward outcome states, GO(�) and GO(�), standing for the more valued and less valued rewards, respectively, and the states of “reward level” (an abstract conception of high and low rewards), R(�) and R(�), standing for high and low rewards, respectively. The states of reward levels are relevant to similarly signed states of reward outcomes. We also assume that in any situation where rewards are allocated, the “ability referential structure” will be automatically salient, so that states of the instrumental characteristic will be relevant to the similarly signed states of reward level. All the elements of this initial structure can be seen in figure 3.

Given the initial structure, the states of the diffuse status characteristic, gender, D(�) and D(�), standing for male and female, respectively, and the states of the nonvalued characteristic, type of instrument, N(a) and N(b), standing for Klee preference and Kandinsky preference, respectively, became salient through the action of the salience process because they discriminate the actors. The actors are connected to these states by possession lines. Since gender is not task relevant, the burden-of-proof process comes into play, the generalized expectations associated with gender are activated, and burden-of-proof paths are established, connecting the actors to the task outcomes. Furthermore, we assume that gender is referentially connected to reward levels, and therefore, a categorical referential structure for gender will become salient, and the states of D will be relevant to reward levels. The resulting situational graph is given in figure

3.

We now need to determine the paths connecting the actors to the outcome states in order to determine their expectations according to the formation of aggregated expectations assumption. We first look at task expectations and see that all paths connecting p to task outcome states, T(�), are positive. We see that p is task connected with two paths of lengths 4 and 5 going through D and C* states, and two other paths of the same lengths going through D and R states, so that

ept(�) p 1 � [1 � f(4)][1 � f(5)][1 � f(4)][1 � f(5)].

We need actual numerical values for the strengths of paths of different lengths to compute the actual expectation value. Fis¸ek, Norman, and Nelson-Kilger (1992) have shown that the function giving these values has a specific form, and the parameters of the form can be determined by making theoretical assumptions about path lengths. We use the function proposed by them:

(2�i)

f(i) p 1 � exp (�2.618 ).

According to this function,

f(4) p .1358, f(5) p .0542,

and therefore,

ept(�) p .332.

Since p does not have any negative paths, this is actually p’s task expectations, ept, and because the graph structure happens to be symmetric, o’s expectations have exactly the same magnitude but is negative in sign. Therefore p’s expectation advantage over o is

tt(�) t(�)

ep�o p ep � eo p .332 � (�.332) p .664.

Turning our attention to the reward expectation advantage, we see that the same general conditions hold: all paths connecting p to reward outcome states, GO(�), are positive and symmetric; that is, o will have exactly the same expectation value as p except for sign. Actor p is connected to reward outcome states with two paths of lengths 3 and 4 through R(�), and two paths of lengths 5 and 6 through C∗(�). Thus the reward expectations of p is given by

epr(�) p 1 � [1 � f(3)][1 � f(4)][1 � f(5)][1 � f(6)].

We need the numerical values of paths of lengths 3 and 6 for this computation:

f(3) p .3175, f(6) p .0211,

and therefore,

epr(�) p .454.

By the same reasoning as in the case of task expectations, the reward expectation advantage of p over o is

epr�o p .908.

To compute the status value association of N(x), we need to note several points. The first is that all paths connecting N(x) to the outcome states (both task and reward) are of positive significance; that is, all paths connecting N(a) to outcome states are positive, and all paths connecting N(b) to the outcome states are negative. Therefore all paths will be combined together according to our combining function. The second thing to note is that each path connecting an actor to an outcome state constitutes a path connecting N(x) to an outcome state of one greater length.

Thus there were two paths of length 4 and two paths of length 5 connecting p to T(�); they constitute two paths of length 5 and two paths of length 6 connecting N(x)to T(�). Since o was task connected by paths of the same lengths that were of negative sign for task expectations, but are of positive significance for status value association, we have four paths of length 5 and four paths of length 6 connecting N(x) to task outcomes. By the same reasoning there are two paths of length 4 and two paths of length 5, and two paths of length 6 (the paths of length 6 connecting actors to reward outcomes drop out as they become paths of length 7) connecting N(x)to GO(�).14 In total there are six paths of length 5 and six paths of length 6 contributing to the status value association of N(x), nN:

66

nN p 1 � [1 � f(5)] [1 � f(6)] p .529.

Figure A1 gives the situational structure after the actors move on to a new task. By the sequence of structure completion assumption, all of the structure developed on the first task remains in the graph, and the salient-ability referential structure establishes two connections of reward levels to the instrumental ability states of the new task. Furthermore the burden-of-proof process establishes the connection of gender to the new task, and the relevance of task outcome states provides the relevance connection between the two task outcome states.

14 Because the f(i) values of extended paths of length 7 and greater are very small, such paths are not included in the calculation of expectation values and status value associations.

Fig. A1.—Male with preference for Klee and female with preference for Kandinsky, after the scenario task, work on a set of cartoons to be used in advertising a different product. Rewards to be given on completion of the task.

The new part of the structure due to the current formulation is the connection of N(x) to the second task because it has acquired status value on the first task. The evaluated states and generalized expectations assumption states that when evaluated states are salient, then generalized expectations will become salient and task connect the evaluated states. However the line connecting the evaluated states to the generalized-expectation states will not be a standard length-1 line, but a variable-length line, depending on the status value association of N(x). These variable-length lines are represented by dashed lines in the graph. The length of the line is given by:

a

l p 1/n .

The parameter a is to be empirically estimated; for our illustrative purposes, to carry out the computations, we will simply assume its value to be one. Therefore,

nN p .529, a p 1,

and

l p 1/.529 p 1.889.

Therefore p is connected to the task outcome with two positive paths of lengths 4.889 and 5.889, and o with two negative lines of the same lengths through the states of N. The strengths of these paths can also be obtained from f(i) as given above; these values are .0601 and .0234. We will not repeat the exercise of tracing paths and computing expectations since no new concepts are involved. We give below the values of the expectation advantages and status value association on the second task.

ept �o p .864, epr �o p 1.012, nN p .568.

We should note that the paths through the evaluated states, N(x), are included in the computations of the expectation advantages, but not in the computation of status value association, since inclusion would bring circularity into the system.

APPENDIX B

The Proofs of the Theorems Below, we will first define a few terms. Then, we will state a basic property of the combining function to facilitate the presentations of the proofs of the theorems.

A status element is normal in situation S, if in the graph representing S, there is no actor for whom there are both positive and negative paths to outcome states containing this element. We shall assume in what follows that all status elements that are being considered are normal.

A t-path is a path connecting an actor or the state of a nonvalued characteristic to a task outcome state; similarly, an r-path is a path connecting an actor or the state of a nonvalued characteristic to a reward outcome state.

An extension of a set of paths is the set of paths obtained by adding an equal number of lines to each path in the set; in particular, a first-order extension is an extension obtained by adding one line to each path. We use the convention that if e is the combined strength of a set of paths, then e� is the combined strength of the first-order extension of that set of paths.

The combining function has the property of preserving order. The simplest example of order preservation is that if two paths are each combined with a third path of the same length, the combined paths will have the same order of strength as the two original paths. A more important instance of this property is that given two sets of paths of differing combined strengths, then the combined strengths of the same-order extension of each will also have the same order of strength.

Proof of theorem 1.—We need to show that the status value association, n,of N is nonzero. That is,

n p (n ∪ �n ) � (n ∪ �n ) 1 0.

a bba

For the components of n, the subscripts indicate the state of the non-valued characteristic, and the superscripts the sign of the paths. Thus, na � is the combined strength of the positive paths linking N(a)tothe outcome states. Each component will have both t-paths and r-paths; however, since normal status elements are hypothesized, we know that the two types of paths will be consistent. Thus it will be sufficient to show that n is nonzero for one type of path; the other type will only increase the magnitude of n. Let us consider t-paths and use n t to stand for the status value association due only to t-paths. We can now write the expression for n t as follows:

t t(�) t(�) t(�) t(�)

n p (e ∪ �e ) � (e ∪ �e ).

p oo p

Because discriminating status elements are hypothesized

t(�) t(�) t(�) t(�)

e p �e and e p �e ,

p oo p

by the order-preservation principle

t(�) t(�) t(�) t(�)

e p �e and e p �e .

poo p

We can rewrite n t as follows:

t t(�) t(�) t(�) t(�)

n p (e ∪ �e ) � (e ∪ �e ).

p po o

Since the expectation advantage of p over o is hypothesized as positive,

t(�) t(�)

ep 1 eo ,

and by the order-preservation principle

t(�) t(�)

ep 1 eo ,

we can conclude that the status value association is greater than zero.

Proof of theorem 2.—Since task and reward expectations are consistent, as in the case of the first theorem, we need only show that the theorem is valid for task expectations. Further, we need only show that the theorem is valid for increasing expectation advantage; the decreasing case will follow by symmetry. Let us denote the original expectations by the subscript “1” and the expectations after new status elements have become salient by the subscript “2.” We want to show that if

et ! et ,

p�o1 p�o2

Diffuse Status Characteristics

then

n t ! n t .

12

Since all characteristics are discriminating, the expectation advantage can be written as

tt(�) t(�)

e p 2e � 2e .

p�op o

Canceling the twos, we can write the antecedent above as

t(�) t(�) t(�) t(�)

e � e ! e � e .

1p 1o 2p 2o

We can rearrange this inequality as below:

t(�) t(�) t(�) t(�)

e � e ! e � e .

2o 1o 2p 1p

The same inequality is going to hold among the first-order extensions of each component expectation:

t(�) t(�) t(�) t(�)

e � e ! e � e .

2o 1o 2p 1p

The result is n1 t ! n2 t, that is,

t(�) t(�) t(�) t(�) t(�) t(�) t(�) t(�)

(e ∪ �e ) � (e ∪ �e ) ! (e ∪ �e ) � (e ∪ �e ).

1p 1o 1o 1p 2p 2o 2o 2p

t(�) t(�) t(�) t(�)

We can simplify this expression as e p e and e p e :

po op

t(�) t(�) t(�) t(�) t(�) t(�) t(�) t(�)

(e ∪ �e ) � (e ∪ �e ) ! (e ∪ �e ) � (e ∪ �e ).

1p 1p 1o 1o 2p 2p 2o 2o

We can rearrange this inequality as

t(�) t(�) t(�) t(�) t(�) t(�) t(�) t(�)

(e ∪ e ) � (e ∪ e ) ! (e ∪ e ) � (e ∪ e ).

2o 2o 1o 1o 2p 2p 1p 1p

We can now see that this inequality can be obtained by combining each component of the final form of the antecedent by itself. Since that operation maintains order, we have obtained the desired result.

Proof of theorem 3.—Let us say that p and o are discriminated by n equally relevant status elements, and that p possesses the negative states of k of these elements. Then we can say that the larger k, the greater the inconsistency; note, however, that since p has expectation advantages over o, k ! n/2. Clearly, maximum consistency is achieved when k p 0, so that the smaller k, the greater the consistency. Therefore, we want to show that the smaller the k, the greater the status value association,

n p (na ∪ �nb ) � (nb ∪ �na ).

Let us say that if the paths connecting N(x) to the outcome states due to one discriminating characteristic state is of strength f, then

2(n�k)2k

n p (1 � (1 � f )) � (1 � (1 � f )),

2k 2(n�k)

n p (1 � f ) � (1 � f ),

2k 2n

n p (1 � f )(1 � (1 � f )).

Clearly, as k decreases, n increases, and this completes the proof.

Proof of theorem 4.—The proof of this theorem follows immediately from first principles; greater relevance means shorter paths connecting N(x) to the task outcomes, and shorter paths mean stronger connections. That is, the total strength of connection due to one discriminating element, f, as we have designated it in the proof of theorem 3, will be greater with greater relevance. We have also shown in theorem 3 that the status value association of N is

2n

n p 1 � (1 � f ),

when p and o are consistently discriminated by n status elements of equal relevance, and f is the strength of connection of each element. Obviously, the larger f, the larger n, which is the assertion of the theorem.

Proof of theorem 5.—Each element will connect p, and therefore N(a), to the outcome states by a number of positive paths, the number being dependent on whether a reward structure is salient or not, and if the reward structure is salient, which referential structures are salient. The length of the paths will also differ, but they will be the same for each characteristic since equal task relevance is hypothesized. Let us say that the positive paths connecting N(a) to the outcome states positively have a combined strength, f, for each characteristic. There will be no negative paths connecting N(a) to the task outcomes. By symmetry, N(b) will be negatively task connected by a set of paths of joint strength �f for each characteristic, and there will be no positive paths connecting N(b)tothe task outcomes.

The expression for status value association,

n p (n � ∪ �n �) � (n � ∪ �n �),

a bba

is simplified since its second term is equal to zero, and if there are n elements, then n is simply equal to the combination of n positive paths of strength f and the negation of n negative paths of strength f. That is,

2n

n p 1 � (1 � f ).

Since f is a quantity less than one, so is (1 � f ), and the second term on the left decreases with increasing n, and therefore n increases with increasing n. This proves the first part of the theorem. To prove the second part, consider three n-values for consecutive values of n:

2n

n1 p 1 � (1 � f ),

2(n�1)

n2 p 1 � (1 � f ),

2(n�2)

n3 p 1 � (1 � f ).

Now consider the differences

2n 2

n1 � n2 p (1 � f )[1 � (1 � f )],

2n 22

n2 � n3 p (1 � f )(1 � f )[1 � (1 � f )],

2n 22n 22

(1 � f )[1 � (1 � f )] 1 (1 � f )(1 � f )[1 � (1 � f )],

1 1 (1 � f)2.

This proves the second part of the theorem.

Proof of theorem 6.—Each one of the actors p through ok will connect N(a) to the outcome states by positive paths, the number of paths will depend on the number of discriminating elements, and the lengths of the paths will depend on the relevance of the elements; however, they will be the same for each actor. Let us denote the combined strength of the paths due to one actor by f. Similarly, each one of the actors ok�1 will connect N(b) to the outcome states by negative paths. By symmetry, the combined strength of the paths due to each actor will be �f. The status value association is given by

n p (n ∪ �n ) � (n ∪ �n ).

a bba

The second term is equal to zero, and the first term is simply the union of all paths, that is,

n

n p 1 � (1 � f ).

Clearly, a increases as n increases. This completes the proof.

Proof of theorem 7.—On the first task, the discriminating characteristics will become outcome connected through the burden-of-proof process, and by hypothesis, p will have task and reward expectation advantages (given a salient reward outcome structure) over o. Therefore, N will become outcome connected by the first-order extensions of the paths connecting p and o to the outcomes, and will acquire status value. On the second task, the discriminating characteristics will again connect to the second set of outcomes, and the actors will be connected to the outcomes in exactly the same way they were connected to the first. The actors will also have further connections, through the task-to-task relevance which is established when tasks are performed in sequence. And these further connections, being consistent with the old, will increase p’s expectation advantages over o. Therefore, by theorem 2, the status value association of N will be higher on the second task than on the first. Now when there is attainment, this will add even further paths to the structure: attainment provides two positive t-paths of lengths 3 and 4, and either two positive r-paths of lengths 4 and 5 (if there is a salient outcome referential structure) or two positive r-paths of lengths 5 and 6 (if there is only the ability referential structure salient) linking N(a) to the outcome states. Paths of the same lengths but of negative sign connect N(b) to the outcome states. These attainment paths contribute to status value association, and therefore status value association will be greater than it would have been without these attainment paths. This completes the proof.

Proof of theorem 8.—The proof is exactly parallel to the proof of theorem 7. Reward allocation creates additional paths in the graph for the second task, just like goal attainment does: goal object allocation provides two positive r-paths of lengths 3 and 4, and either two positive t-paths of lengths 4 and 5 (if there is a salient outcome referential structure) or two positive t-paths of lengths 5 and 6 (if there is only the ability referential structure salient) linking N(a) to the outcome states. Paths of the same length but of negative sign connect N(b) to the outcome states. All these paths contribute to status value association, and therefore, it will be greater than it would have been without these additional reward allocation paths. This completes the proof.

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