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This list of List Servers, or Listserv discussion groups, indicate the popularity of such communication vehicles. The format for each entry is: List-

Name followed by a brief one-phrase description. The second line is the Internet subscription address. Unless otherwise noted, anyone can subscribe by sending a one-line message to these addresses. The one-line message should say ‘‘subscribe’’ followed by the List-Name.

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In contrast to Internet Mailing Lists, UseNet

Newsgroups do not broadcast a message to all those included on the list. Internet users must specifically access the postings (messages) for any such newsgroup. While on any given day, ‘‘sociology’’ will be mentioned in a variety of newsgroup discussions, the only newsgroup where academic sociological topics are regularly discussed is: alt.sci.sociology. Generally a few messages are added to this discussion area every day.

RONALD E. ANDERSON

CONFIDENCE INTERVALS

See Statistical Inference.

CONFLICT THEORY

NOTE: Although the following article has not been revised for this edition of the Encyclopedia, the substantive coverage is currently appropriate. The editors have provided a list of recent works at the end of the article to facilitate research and exploration of the topic.

Conflict theory explains social structure and changes in it by arguing that actors pursue their interests in conflict with others and according to their resources for social organization. Conflict theory builds upon Marxist analysis of class conflicts, but it is detached from any ideological commitment to socialism. Max Weber generalized con-

flict to the arenas of power and status as well as economic class, and this multidimensional approach has become widespread since the 1950s.

WHAT CONSTITUTES A CONFLICT

GROUP?

For Marx and Engels, a society’s conflicting interests derive from the division between owners and nonowners of property. Dahrendorf (1959) proposed that conflicts are based on power, dividing order-givers, who have an interest in maintaining the status quo, from order-takers, who have an interest in changing it. Property is only one of the bases of power conflict, and conflicts can be expected inside any type of organization, including socialist ones. In the Weberian model there are even more types of conflict, since every cultural group (such as ethnic, religious, or intellectual groups) can also struggle for advantage. In addition, economic conflict takes place in three different types of market relations, pitting employers against workers, producers against consumers, and lenders against borrowers (Wiley 1967). Gender stratification produces yet another dimension of conflict.

THE PROCESS OF CONFLICT

Conflicting interests remain latent until a group becomes mobilized for active struggle. This occurs when its members are physically concentrated, have material resources for communicating among themselves, and share a similar culture. The higher social classes are typically more mobilized than lower classes, and most struggles over power take place among different factions of the higher classes. Lower classes tend to be fragmented into localized groups and are most easily mobilized when they are a homogeneous ethnic or religious group concentrated in a particular place. The better organized a conflict group is, the longer and more intensely it can struggle; such struggles become routinized, as in the case of entrenched labor unions or political parties. Less organized conflict groups that become temporarily mobilized are more likely to be violent but unable to sustain the conflict.

Overt conflict increases the solidarity of groups on both sides. Coser (1956), elaborating the theory of Georg Simmel, points out that conflict leads to a centralization of power within each group and motivates groups to seek allies. A conflict thus tends to polarize a society into two factions, or a world of warring states into two alliances. This

process is limited when there are cross-cutting memberships among groups, for instance, if class, ethnic, and religious categories overlap. In these cases, mobilization of one line of conflict (e.g., class conflict) puts a strain on other dimensions of conflict (e.g., ethnic identity). Thus, cross-cutting conflicts tend to neutralize each other. Conversely, when multiple lines of group membership are superimposed, conflicts are more extreme.

Conflicts escalate as each group retaliates against offenses received from the other. How long this process of escalation continues depends on how much resources a group can draw upon: its numbers of supporters, its weapons, and its economic goods. If one group has many more resources than the other, the conflict ends when the mobilizing capacity of the weaker side is exhausted. When both sides have further resources they have not yet mobilized, escalation continues. This is especially likely when one or both sides have sustained enough damage to outrage and mobilize their supporters but not great enough damage to destroy their organizational resources for struggle.

Deescalation of conflict occurs in two very different ways. If one side has overwhelming superiority over the other, it can destroy opposition by breaking the other group’s organizational capacity to fight. The result is not harmony but an uneasy peace, in which the defeated party has been turned back into an unmobilized latent interest. If neither side is able to break up the other’s organization, conflict eventually deescalates when resources are eaten up and the prospects of winning become dimmer. Although wars usually arouse popular solidarity at first, costs and casualties reduce enthusiasm and bring most wars to an end within a few years. Civilian uprisings, strikes, and other small-scale conflicts typically have fewer resources to sustain them; these conflicts deescalate more quickly. During a deescalation, the points of contention among the opponents modulate from extreme demands toward compromises and piecemeal negotiation of smaller issues (Kriesberg 1982).

Very destructive levels of conflict tend to end more rapidly than moderate conflicts in which resources are continuously replenished.

COERCIVE POWER AND REVOLUTION

In a highly coercive state, such as a traditional aristocracy or a military dictatorship, power is

organized as an enforcement coalition (Collins 1988; Schelling 1962). Members of the ruling organization monitor each other to ensure loyalty. A change in power is possible only when a majority of the enforcers disobey orders simultaneously. Revolts occur in a rapid ‘‘bandwagon effect,’’ during which most members scramble to become part of the winning coalition. The more coercive the state, the more extreme the swings between long periods of tyrannical stability and brief moments of political upheaval.

Since the state claims a monopoly on the instruments of violence, revolutionary changes in power occur through the reorganization of coercive coalitions. Revolts from below are almost always unsuccessful as long as the state’s military organization stays intact. For this reason, revolutions typically are preceded by a disintegration of the military, due to defeat in war, depletion of economic resources in previous conflicts, and splits within the ruling group (Skocpol 1979). These breakdowns of military power in turn are determined by geopolitical processes affecting the expansion or contraction of states in the surrounding world (Stinchcombe 1968; Collins 1986).

WHO WINS WHAT?

Conflict shapes the distribution of power, wealth, and prestige in a society. The victorious side is generally the group that is better mobilized to act in its collective interest. In many cases, the dominant group is well organized, while the opposing interest group remains latent. The result is a stable structure of stratification, in which overt conflict rarely occurs.

Lenski (1966) showed that concentration of wealth throughout world history is determined by the interaction of two factors. The higher the production of economic surplus (beyond what is necessary to keep people alive), the greater the potential for stratification. This surplus in turn is appropriated according to the distribution of power.

Turner (1984) theorizes that the concentration of power is unequal to the extent that there is external military threat to the society or there is a high level of internal conflict among social groups.

Both external and internal conflict tend to centralize power, providing that the government wins

these conflicts; hence, another condition must also be present, that the society is relatively productive and organizationally well integrated. If the state has high resources relative to its enemies, conflict is the route by which it concentrates power in its own hands.

Prestige is determined by the concentration of power and wealth. Groups that have these resources can invest them in material possessions that make them impressive in social encounters. In addition, they can invest their resources in cultureproducing organizations such as education, entertainment, and art, which give them cultural domination. According to Pierre Bourdieu’s research

(1984), the realm of culture is stratified along the same lines as the stratification of the surrounding society.

EFFECTS OF CONFLICT GROUPS UPON

INDIVIDUALS

The latent lines of conflict in a society divide people into distinctive styles of belief and emotion. Collins (1975) proposed that the differences among stratified groups are due to the microinteractions of daily experience, which can occur along the two dimensions of vertical power and horizontal solidarity. Persons who give orders take the initiative in the interaction rituals described by Goffman (1959). These persons who enact the rituals of power identify with their frontstage selves and with the official symbols of the organizations they control; whereas persons who take orders are alienated from official rituals and identify with their private, backstage selves. Individuals who belong to tightly enclosed, localized groups emphasize conformity to the group’s traditions; persons in such positions are suspicious of outsiders and react violently and emotionally against insiders who are disrespectful of the group’s symbols. Loosely organized networks have less solidarity and exert less pressure for conformity. Individuals build up emotional energy by microexperiences that give them power or solidarity, and they lose emotional energy when they are subordinated to power or lack experiences of solidarity (Collins 1988). Both emotions and beliefs reproduce the stratification of society in everyday life.

REFERENCES

Bailey, Kenneth D. 1997 ‘‘System and Conflict: Toward a Symbiotic Reconciliation.’’ Quality and Quantity 31:425–442.

Bourdieu, Pierre 1984 Distinction. Cambridge, Mass.:

Harvard University Press.

Briggs, E. Donald 1992 ‘‘New Directions in Conflict Theory: Conflict Resolution and Conflict Transformation.’’ Canadian Journal of Political Science / Revue canadienne de science politique 25:430–431.

Chapin, Mark 1994 ‘‘Functional Conflict Theory, the Alcohol Beverage Industry, and the Alcoholism Treatment Industry.’’ Journal of Applied Social Sciences

18:169–182.

Collins, Randall 1975 Conflict Sociology. New York: Aca-

demic Press.

———1986 Weberian Sociological Theory. Cambridge: Cambridge University Press.

———1988 Theoretical Sociology. San Diego: Harcourt Brace Jovanovich.

Collins, Randall 1993 ‘‘What Does Conflict Theory Predict about America’s Future?’’ Sociological Perspectives 36:289–313.

Coser, Lewis A. 1956 The Functions of Social Conflict. New York: Free Press.

Schelling, Thomas C. 1962 The Strategy of Conflict.Cambridge, Mass.: Harvard University Press.

Skocpol, Theda 1979 States and Social Revolutions. New York: Cambridge University Press.

Stinchcombe, Arthur L. 1968 Constructing Social Theo-

ries. New York: Harcourt.

Turner, Jonathan H. 1984 Societal Stratification: A Theoretical Analysis. New York: Columbia University Press.

——— 1993 Classical Sociological Theory: A Positivist’s Perspective. Chicago, Ill.: Nelson-Hall Publishers.

Van-Huyssteen, Elsa F. 1994 ‘‘Interpretation of the South African Legal System in Terms of the Analytical Conflict Perspective.’’ Suid Afrikaanse Tydskrif vir Sosiologie / South African Journal of Sociology 25:87–94.

Wiley, Norbert F. 1967 ‘‘America’s Unique Class Politics: The Interplay of the Labor, Credit, and Commodity Markets.’’ American Sociological Review

32:529–540.

RANDALL COLLINS

CONSISTENCY THEORY

See Cognitive Consistency Theories.

Dahrendorf, Ralf 1959 Class and Class Conflict in Industrial Society. Stanford, Calif.: Stanford University Press.

Gagnon, V. P., Jr. 1995 ‘‘Ethnic Conflict as an IntraGroup Phenomenon: A Preliminary Framework.’’

Revija za Sociologiju 26:1–2.

Glaser, James M. 1994 ‘‘Back to the Black Belt: Racial Environment and White Racial Attitudes in the South.’’ Journal of Politics 56:21–41.

Goffman, Erving 1959 The Presentation of Self in Everyday Life. New York: Doubleday.

Hanneman, Robert A., Randall Collins, and Gabriele Mordt 1995 ‘‘Discovering Theory Dynamics by Computer Simulation: Experiments on State Legitimacy and Imperialist Capitalism.’’ Sociological Methodology 25:1–46.

Haugaard, Mark 1997 ‘‘The Consensual Basis of Conflictual Power: A Critical Response to ‘Using Power, Fighting Power’ by Jane Mansbridge.’’ Constellations 3:401–406.

Kriesberg, Louis 1982 Social Conflicts. Englewood Cliffs,

N.J.: Prentice-Hall.

CONTENT ANALYSIS

‘‘Content analysis’’ has evolved into an umbrella label that includes various procedures for making reliable, valid inferences from qualitative data, including text, speech, and images. These procedures have improved and expanded due to numerous developments in recent years since this encyclopedia’s first edition.

Traditionally, ‘‘content analysis’’ has referred to systematic procedures for assigning prespecified codes to text, such as interviews, newspaper editorials, open-ended survey answers, or focus-group transcripts, and then analyzing patterns in the codings. Some projects will count each specific occurrence within a text, while others will have coders tally the number of column inches assigned a code. Either way, the procedure usually employs

a ‘‘top down’’ strategy, beginning with a theory and hypotheses to be tested, developing reliable coding categories, applying these to coding-speci- fied bodies of text, and finally testing the hypotheses by statistically comparing code indexes across documents.

With the increasing popularity of qualitative sociology, content analysis has also come to refer to ‘‘grounded’’ inductive procedures for identifying patterns in various kinds of qualitative data including text, illustrations, and videos. For example, the data might include observers’ detailed notes of children’s behaviors under different forms of supervision, possibly supplemented with videotapes of those same behaviors. While traditional content analysis usually enlisted statistical analyses to test hypotheses, many of these researchers do not start with hypotheses, but carefully search for patterns in their data.

However, rather than just produce statistical analyses or search for patterns, investigators should also situate the results of a content analysis in terms of the contexts in which the documents were produced. A content-analysis comparison of letters to stockholders, for example, should take into consideration the particular business sectors covered and the prevailing economic climates in which they were written. An analysis of American presidential nomination acceptance speeches should consider that they changed dramatically in form once they started to be broadcast live on national radio. A content analysis may have reliable coding, but the inferences drawn from that coding may have little validity unless the researcher factors in such shaping forces.

Like any expanding domain, there has been a tendency for content analysis to segment into specialized topics. For example, Roberts (1997) focuses on drawing statistical inferences from text, including Carley’s networking strategies and Gottschalk’s clinical diagnostic tools. There also has been a stream of instructional books, including several series published by Sage, that focus on particular kinds of qualitative data such as focusgroup transcripts. A technical literature also has developed addressing specialized computer software and video-analysis techniques. Nevertheless the common agenda is analyzing the content of qualitative data. Inasmuch as our lives are shaped

by different forms of media, and inasmuch as different analytic procedures can complement one another in uncovering important insights, it makes sense to strive toward an integration, rather than fragmentation.

Many advances in content-analysis procedures have been made possible by the convenience and power of desktop and laptop computers. In addition, an overwhelming proportion of text documents are now generated on computers, making their text files computer accessible for content analysis. And a revolution in hand-held analogue and digital video cameras, together with comput- er-based technology for editing and analyzing videotapes, makes new research procedures feasible.

Consider, for example, new possibilities for analyzing responses to open-ended questions in survey research. For years, survey researchers have been well aware that closed-ended questions require respondents to frame how they think about an issue in terms of a question’s multiple choices, even when the choice options had little to do with how a respondent views an issue. But the costs and time involved in analyzing open-ended responses resulted in such questions rarely being used. Even when they were included in a survey, the interviewers usually just recorded capsule summaries of the responses that omitted most nuances of what was said.

Contrast this then with survey research using today’s audio information-capturing technologies. Telephone survey interviewers are guided by instructions appearing on a computer screen. Whenever an open-ended question appears, the interviewer no longer needs to type short summaries of the responses. Instead, a computer digitally captures an audio recording of each open-ended response, labels it, and files it as a computer record.

Any audio response can later be easily fetched and replayed, allowing a researcher, for example, to identify a ‘‘leaky voice,’’ that is, one indicative of the respondent’s underlying emotion or attitude.

And the full audio responses are then available to be transcribed to text, including, if desired, notations indicating hesitations and voice inflections. Until computer voice recognition is completely reliable, transcribing usually remains a manual task. But with spreadsheet software (such as Excel) no longer restrictively limiting the amount of text

in any one cell, the text of each individual’s entire response to a question can be placed in a spreadsheet cell, thus capturing both the closed-ended and open-ended data for a survey into a convenient, single spreadsheet for researchers to analyze.

With the survey data in this convenient form, researchers can then code open-ended responses manually, putting their assigned codes in additional spreadsheet columns. As a teaching exercise, it is instructive to assign students a task such as identifying gender differences among a thousand responses to a broad open-ended question, such as a question asking respondents’ views about peace or family values. Students first might sort the spreadsheet by gender in order to read separately samples of male responses and female responses and obtain a sense of what possible gender differences exist. They then develop coding instructions that capture these differences and apply the codes to the entire set of responses. This coding, of course, is better done without knowledge of the respondents’ genders, with responses in a random order, and on different respondents than those used to develop the codes. After coding several hundred responses, however, students usually begin to glaze over and soon the most ardent humanist student is asking whether the computer could possibly be of help in assigning codes.

For some kinds of coding, computer help is indeed available in the form of computer programs that assign codes. Such codings can be treated as advisory and then manually confirmed, augmented perhaps by also assigning a weight. Or they may be used as is after being spot-checked for accuracy. Not only can a computer complete huge amounts of tedious coding in minutes, possibly assigning many different types of codings to each text, but these codings may uncover statistically significant frequency differences that human coders would not uncover, if only because computer analysis is so even-handed and untiring. The static created by occasional miscodings may be more than offset by gains from a reliable consistency in making many codings.

Computer coding assignments are usually based on the occurrence of words, particular senses of words, or multiword idioms appearing in the text. For example, the word ‘‘father’’ in a text might be coded as ‘‘male,’’ ‘‘family member,’’ etc. as well as

possibly ‘‘authority-role.’’ Computer content-analy- sis software may search the contexts of words in the text to ferret out and correctly code common word senses. For example, for a national study of people’s perceptions of African-American young males on several open-ended questions, it was particularly important for the computer to identify correctly each respondent’s usages of such mul- ti-meaning words as ‘‘race,’’ ‘‘white,’’ ‘‘black,’’ and ‘‘color.’’

In addition to developing their own coding categories, researchers may enlist existing com- puter-scored categories that are relevant to the task at hand. For example, it might be hypothesized that one group being studied is more optimistic and its responses will reflect more ‘‘positive thinking’’ while another is more negative or pessimistic. To code ‘‘positive thinking’’ a researcher may want the computer to apply an existing con- tent-analysis category that includes over 1200 words, word roots, word senses, phrasal verbs, and idioms, thus essentially covering most expressions of ‘‘positive-thinking’’ that occur as infrequently as three times per million words of ordinary English text. A similar category exists for negative-think- ing, allowing the investigator to check whether the groups being studied differ in their coded positive thinking, negative thinking, or both. And by enlisting such standard categories, the results obtained in one study can be readily compared with results found in other studies.

Once data has been captured in a convenient format for computer use, they can be repeatedly analyzed. For example, should our now glazedover students have any energy left after analyzing the responses by gender, they could be given an additional assignment of identifying and coding rural-urban differences in these same open-ended responses. Given so many analyses that can be made, it makes sense to let the computer do what it can, saving manual labor for those types of codings that would be hard to have a computer assign. Even multimedia qualitative-analysis software such as HyperResearch includes some rudimentary tools for automatic assignments.

Moreover, desktop computer software has also become available that identifies patterns in text without having to develop coding categories. For example, SPSS’s TextSmart uses an algorithm that

groups respondents into clusters based on worduse co-occurrences within responses and then maps these clusters into a two-dimensional grid that uses colors to represent each cluster group. If such an automated inductive procedure can produce additional valid insights that other techniques are likely to overlook, then why not use it too?

Pioneering work in inductive automatic categorizing, such as Iker’s (1969), usually enlisted procedures based upon correlation matrixes, such as factor analysis. These procedures tended not to be particularly suited to analyzing text both because of the shape of word-usage frequency distributions as well as the limited number of words that a correlation matrix could feasibly handle. TextSmart, based upon a word-distance measure, provides much more suitable solutions. Further automatic categorizing procedures may be expected from artificial intelligence, as well as from categorizing techniques being developed for Internet search engines.

Content-analysis research strategies can thus now easily be multipronged, spanning from completely automatic inductive procedures to manual coding. But even manual coding these days is likely to utilize computer software to help coders manage information. Consider these changes in costs and convenience: Unlike mainframe computing of the 1960s and 1970s, when the cost of an hour of computer time was about the same as a coder’s wage for several weeks, the marginal cost of using a desktop computer is essentially the electricity it uses. Today’s desktop computer is likely to be more than fivefold faster at content-analysis coding than those mainframe computers ever were.

They also can access much larger dictionaries and other information in their RAM than was ever feasible on a user partition of a mainframe computer, thus making their coding more accurate and comprehensive. Moreover, a single CD-ROM full of text to be analyzed is easily popped into a desktop computer, whereas in the days of mainframe computing, a comparable amount of text would have to be keypunched on over 3,000 boxes of IBM cards.

Given today’s convenience and low cost of computer-based procedures, there is no reason to limit an analysis to one approach, especially if insights gained from one approach will differ and

often complement those gained from another. Instead of being limited by technology, the limits now may lie in the skills, proclivities, and comfort zones of the researchers. Research teams, rather than individual researchers, may prove the best solution, for only in a team made up of people with complementary strengths is one likely to find the full range of statistical, conceptual, intuitive, experiential, and perhaps clinical strengths needed to carry out penetrating, comprehensive content-analy- sis projects. Moreover, some researchers will prefer to learn from the main trends while others will learn more from studying outlying cases. Some will learn from bottom-line numbers while others will learn more from innovative graphics that highlight information patterns. Some will focus on current data while others will contextualize data historically by comparing them with data in archives. Data that has been gathered and assembled at considerable cost, especially data-gathering that imposed on many respondents, merit as thorough and comprehensive analyses as these various procedures collectively offer.

Unfortunately, however, an ‘‘either-or’’ assumption about how to do content analysis has continued to be supported both by books and computer software. Authors who do an excellent job of describing one approach to content analysis, such as Boyatzis (1998), give an impression that an either-or decision has to be made about which approach to use. Some software—especially that ported from mainframe computers or developed for early desktop computers—still may steer or even limit researchers who use it to just one approach. For example, some software packages create specialized data formats such as ‘‘classification trees’’ that then in effect constrain the user to analyses that can be readily derived from that format. Software reviews such as Lewis’s (1998) excellent comparison of ATLAS/ti and NUD-IST software have been explicit about what assumptions a researcher buys into when utilizing each package.

Additional leverage in analyzing qualitative information has stemmed from computer-based tools, such as newer versions of HyperResearch and ATLAS/ti, that integrate the handling of multiple media (text, illustrations, and video). Especially as more software comes from countries where there are expert programming skills and programming

labor is relatively inexpensive, we can expect ambitious content-analysis software, of which TextAnalyst from Russia (www.megaputer.com) may be a forerunner.

Given continuing content-analysis software developments, those who would like to learn what is currently available are advised search Internet sites rather than rely upon even recently published materials. One recommended starting point is the Georgia State University content-analysis site (www.gsu.edu/~wwwcom/content.html), which gives links to software web sites (including software mentioned in this article), indexes recent contentanalysis publications, and has a mailing list of more than 700 members. Technical reviews of relevant language-analysis tools, such as Berleant’s (1995), occasionally appear in computational linguistics journals and web sites. For training, the University of Essex Summer School in Social Science Data Analysis and Collection (www.essex.ac.uk), as part of a program of a European consortium, has been offering a content-analysis module for years as part of its program.

Given the developments described here, some of the contributions that content analysis should be able to make to sociological research include:

1.A major shift from reliance upon closedended questions to an appropriate use of open-ended questions that lets people be heard in the ways they frame issues, as well as the way they think and feel

about them, as discussed in detail by

Stone (1997)

2.A better understanding of both print and television media and its impact on public opinion, both in setting agendas and in influencing opinion intensity, as laid out in Neuman (1989). This will involve research that compares the content of media with the content of opinions. Not only will survey research data be archived and accessible from Internet servers, but full-display media will be accessible from Lexis-Nexis and on-line editions supplied by media providers, as well as television news archives such as those at Vanderbilt

University

3.Better use of historical qualitative data, including both text and graphic materials,

to address such issues as how economic cycles impact ideology, as examined by

Namenwirth and Weber (1987), or to uncover cycles of creativity, as demonstrated by Martindale (1990)

4.Investigations, several of which are already underway, of both intranet communication patterns within organizations as well as Internet communications, including analyses of the content of communications over those networks.

There is also, however, good reason for caution. Never before in history has so much qualitative information been available electronically. Highvolume image scanning will also further increase the amount of information that can be electronically accessed and content-analyzed. Quite understandably, those agencies responsible for limiting terrorist activities may look on content-analysis procedures as possibly providing early warnings that could save lives. But these procedures can also become tools for a ‘‘big-brother’’ monitoring society. Sociologists have an important role in anticipating these problems and helping resolve them.

REFERENCES

Berleant, Daniel 1995 ‘‘Engineering ‘Word Experts’ for Word Disambiguation.’’ Natural Language Engineering 1 (4):339–362.

Boyatzis, Richard E. 1998 Transforming Qualitative Information: Thematic Analysis and Code Development. Thousand Oaks, Calif.: Sage.

Iker, Howard, and Norman Harway 1969 ‘‘A Computer Systems Approach Toward the Recognition and Analysis of Content.’’ In George Gerbner, Ole Hosti, Klaus Krippendorff, William Paisley, and Philip Stone, eds.,

The Analysis of Communication Content. New York: Wiley.

Lewis, R. Berry 1998 ‘‘ATLAS/ti and NUD-IST: A Comparative Review of Two Leading Qualitative Data Analysis Packages.’’ Cultural Anthropology Methods 10 (3):41–47.

Martindale, Colin 1990 The Clockword Muse: The Predictability of Artistic Change. New York: Basic Books.

Namenwirth, J. Zvi, and Robert Philip Weber 1987 Dynamics of Culture. Winchester, Mass.: Allen and Unwin.

Neuman, Richard 1989 ‘‘Parallel Content Analysis: Old Paradigms and New Proposals.’’ Public Communication and Behavior 2:205–289.

Roberts, Carl W. (ed.) 1997 Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts. Mahwah, N.J.: Lawrence Erlbaum.

Stone, Philip J. 1997 ‘‘Thematic Text Analysis: New Agendas for Analyzing Text Content.’’ In Carl W. Roberts, ed., Text Analysis for the Social Sciences: Methods for Drawing Statistical Inferences from Texts and Transcripts. Mahwah, N.J.: Lawrence Erlbaum.

PHILIP STONE

CONTINGENCY TABLES

See Tabular Analysis; Typologies.

CONVERGENCE THEORIES

The idea that societies move toward a condition of similarity—that they converge in one or more respects—is a common feature of various theories of social change. The notion that differences among societies will decrease over time can be found in many works of eighteenth and nineteenth century social thinkers, from the prerevolutionary French philosophes and the Scottish moral philosophers through de Tocqueville, Toennies, Maine,

Marx, Spencer, Weber, and Durkheim (Weinberg

1969; Baum 1974). More recently, the study of ‘‘postindustrial’’ society and the debate over ‘‘postmodernist’’ aspects of contemporary society also reflect to some degree the idea that there is a tendency for broadly similar conditions or attributes to emerge among otherwise distinct and dissimilar societies.

In sociological discourse since the 1960s, the term convergence theory has carried a more specific connotation, referring to the hypothesized link between economic development and concomitant changes in social organization, particularly work and industrial organization, class structure, demographic patterns, characteristics of the family, education, and the role of government in assuring basic social and economic security. The core notion of convergence theory is that as nations achieve similar levels of economic development they will become more alike in terms of these (and other) aspects of social life. In the 1950s and 1960s, predictions of societal convergence were most

closely associated with modernization theories, which generally held that developing societies will follow a path of economic development similar to that followed by developed societies of the West. Structural-functionalist theorists, such as Parsons (1951) and Davis (1948), while not actually employing the terminology of convergence theory, paved the way for its development and use in modernization studies through their efforts to develop a systematic statement of the functional prerequisites and structural imperatives of modern industrial society; these include an occupational structure based on achievement rather than ascription, and the common application of universalistic rather than particularistic evaluative criteria. Also, beginning in the 1960s, convergence theory was invoked to account for apparent similarities in industrial organization and patterns of stratification found in both capitalist and communist nations (Sorokin 1960; Goldthorpe 1964;

Galbraith 1967).

CONVERGENCE THEORY AND

MODERNIZATION

The conventional and most controversial application of convergence theory has been in the study of modernization, where it is associated with the idea that the experience of developing nations will follow the path charted by Western industrialized nations. Related to this idea is the notion of a relatively fixed pattern of development through which developing nations must pass as they modernize (Rostow 1960). Inkeles (1966), Inkeles and

Smith (1974), and Kahl (1968) pursued the idea of convergence at the level of individual attitudes, values, and beliefs, arguing that the emergence of a ‘‘modern’’ psychosocial orientation accompanies national modernization (see Armer and

Schnaiberg 1972 for a critique).

Kerr and colleagues’ Industrialism and Industrial Man (1960) offers the classic statement of the ‘‘logic of industrialism’’ thesis, which the authors proposed as a response to Marxian theory’s equation of industrial society with capitalism. More specifically, Kerr et al. sought to identify the ‘‘inherent tendencies and implications of industrialization for the work place,’’ hoping to construct from this a portrait of the ‘‘principal features of the new society’’ (p. 33). The features common to

industrial society, they argued, include rapid changes in science, technology, and methods of production; a high degree of occupational mobility, with continual training and retraining of the work force; increasing emphasis on formal education, particularly in the natural sciences, engineering, medicine, managerial training, and administrative law; a workforce highly differentiated in terms of occupational titles and job classifications; the increasing importance of urban areas as centers of economic activity; and the increasing role of government in providing expanded public services, orchestrating the varied activities of a large and complex economy, and administering the ‘‘web of rules’’ of industrial society. Importantly, Kerr et al. envisioned these developments as cutting across categories of political ideology and political systems.

Although the ‘‘logic of industrialism’’ argument is often cited as a prime example of convergence theory (see Form 1979; Moore 1979; Goldthorpe 1971), Kerr et al. never explicitly made this claim for their study. While mentioning convergence at various points in their study, the authors pay equal attention to important countercurrents leading toward diverse outcomes among industrial societies. The concluding chapter of

Industrialism and Industrial Man is, in fact, entitled ‘‘Pluralistic Industrialism,’’ and addresses the sources of diversity as well as uniformity among industrial societies. Among sources of diversity identified are the persistence of existing national institutions, enduring cultural differences, variations in the timing of industrialization (late versus early), the nature of a nation’s dominant industry, and the size and density of population. Counterposed against these factors are various sources of uniformity, such as technological change, exposure to the industrial world, and a worldwide trend toward increased access to education leading to an attenuation of social and economic inequality.

The critique of convergence theory in the study of modernization recalls critiques of earlier theories of societal evolution advanced under the rubric of social Darwinism in the nineteenth century and structural functionalism in the mid-twen- tieth century. The use of convergence theory to analyze modernization has been attacked for its alleged assumptions of unilinearity and determinism (i.e., a single path of development that all societies must follow), its teleological or historicist

character (Goldthorpe 1971), its Western ideological bias (Portes 1973), and for ignoring the structurally dependent position of less-developed countries in the world economy (Wallerstein 1974). Yet a careful review of the literature suggests that many criticisms have often tended to caricature convergence theory rather than addressing its application in actual research studies. Since the 1960s few if any researchers have explicitly claimed convergence theory, at least in its unreconstructed form, as their own. For example, Moore (1979), an exponent of the ‘‘conventional’’ view of modernization, subtitled his book, World Modernization, ‘‘the limits of convergence,’’ and went to great pains to distance himself from the ‘‘model modernized society’’ position associated with early versions of convergence theory (see Moore 1979, pp. 26–28, 150–153). And Parsons (1966), whose name is virtually synonymous with structural functionalism, concluded one of his later writings on comparative sociology with the statement that ‘‘any linear theory of societal evolution’’ is ‘‘untenable’’

(p. 114). As Form (1979) observes, convergence theory passed through a cycle typical of social science theories: a burst of initial interest and enthusiasm, followed by intense criticism and controversy, finally giving way to neglect. The major challenge to those wishing to revive convergence theory and rescue it from its critics is to specify its theoretical underpinnings more precisely, to develop appropriate empirical studies, and finally account for variation as well as similarity among observed cases.

FORMS OF CONVERGENCE AND

DIVERGENCE

In recent years Inkeles (1980, 1981; also Inkeles and Sirowy 1983) has made the most systematic attempt to reformulate convergence theory and respecify its core hypotheses and propositions. Inkeles (1981) argues that earlier versions of convergence theory failed to distinguish adequately between different elements of the social system, which is problematic because these elements not only change at different speeds, but may move in opposite directions. He proposes dividing the social system into a minimum of five elements for purposes of assessing convergence: modes of production and patterns of resource utilization; institutional arrays and institutional forms; structures