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Hedges et al. 1992; Johnson et al. 1995). As a test for significance of this weighted mean effect size, a confidence interval is typically computed around this mean, based on its standard deviation, d+ ± 1.96 √v+, where 1.96 is the unit-normal value for a 95 percent confidence interval (CI) (assuming a nondirectional hypothesis). If the CI includes zero (0.00), the value indicating exactly no difference, it may be concluded that aggregated across all studies there is no significant association between the independent and dependent variables (X and Y). For example, Perkins and colleagues (1995) found no evidence across thirteen studies that silicone breast implants increased risk of connective tissue disease. In a different literature, He and colleagues (1999) found that, across eighteen studies, nonsmokers exposed to passive smoke had a higher relative risk of coronary heart disease than nonsmokers not exposed to smoke.

Once a meta-analysis has derived a weighted mean effect size, it, and other meta-analytic statistics, must be interpreted and presented, which is the seventh step of conducting a meta-analysis. If the mean effect is nonsignificant and the homogeneity statistic is small and nonsignificant, an analyst might conclude that there is no relation between the variables under consideration. However, in such cases, it is wise to consider the amount of statistical power that was available: If the total number of research participants in the studies integrated was small, it is possible that additional data would support the existence of the effect. Even if the mean effect is significant and the homogeneity statistic is small and nonsignificant, concerns about its magnitude arise. To address this issue, Cohen (1969, 1988) proposed some guidelines for judging effect magnitude, based on his informal analysis of the magnitude of effects commonly yielded by psychological research. Cohen intended ‘‘that medium represent an effect of a size likely to be visible to the naked eye of a careful observer’’ (1992, p. 156). He intended that small effect sizes be ‘‘noticeably smaller yet not trivial’’ (p. 156) and that large effect sizes ‘‘be the same distance above medium as small is below it’’ (p. 156). As Table 1 shows, a ‘‘medium’’ effect turned out to be about d = 0.50 and r = .30, equivalent to the difference in intelligence scores between clerical and semiskilled workers. A ‘‘small’’ effect size was about d = 0.20 and r = .10, equivalent

Cohen's (1969) Guidelines for Magnitude of d and r

Table 1

to the difference in height between 15and 16- year-old girls. Finally, a large effect was about d = 0.80 and r = .50,equivalent to the difference in intelligence scores between college professors and college freshmen.

Another popular way to interpret mean effect sizes is to derive the equivalent r and square it. This procedure shows how much variability would be explained by an effect of the magnitude of the mean effect size. Thus, a mean d of 0.50 produces an R2 of .09. However, this value must be interpreted carefully because R2, or variance explained, is a directionless effect size. Therefore, if the individual effect sizes that produced the mean effect size varied in their signs (i.e., if the effect sizes were not all negative or all positive), the variance in Y explained by the predictor X, calculated for each study and averaged, would be larger than this simple transformation of the mean effect size. Thus, another possible procedure consists of computing R2 for each individual study and averaging these values.

When the weighted mean effect size and the CI are computed, the homogeneity of the d’s is statistically examined, in order to determine whether the studies can be adequately described by a single effect size (Hedges and Olkin 1985). If the effect sizes can be so described, then they would differ only by unsystematic sampling error. If there is a significant fit statistic, the weighted mean effect size may not adequately describe the outcomes of the set of studies because it is likely that quite different mean effects exist in different groups of studies. Further explanatory work would be merited, even when the composite effect size is significant. The magnitude of individual study outcomes would differ systematically, and these

differences may include differences in the direction (or sign) of the relation. In some studies, the independent variable might have had a large positive effect on the dependant variable, and in other studies, it might have had a smaller positive effect or even a negative effect. Even if the homogeneity test is nonsignificant, significant moderators could be present, especially when the fit statistic is relatively large (for further discussions, see Johnson and Turco 1992; Rosenthal 1995). Nonetheless, in a meta-analysis that attempts to determine the relation of one variable to another, rejecting the hypothesis of homogeneity could be troublesome, because it implies that the association between these two variables likely is complicated by the presence of interacting conditions. However, because analysts usually anticipate the presence of one or more moderators of effect size magnitude, establishing that effect sizes are not homogeneous is ordinarily neither surprising nor troublesome.

To determine the relation between study characteristics and the magnitude of the effect sizes, both categorical models and continuous models can be tested. In categorical models, analyses may show that weighted mean effect sizes differ in magnitude between the subgroups established by dividing studies into classes based on study characteristics. In such cases, it is as though the metaanalysis is broken into sub-meta-analyses based on their methodological features. For example, He and colleagues (1999) found that risk of coronary heart disease was greater for women than for men nonsmokers who were exposed to passive smoke. If effect sizes that were found to be heterogeneous become homogeneous within the classes of a categorical model, the relevant study characteristic has accounted for the systematic variability between the effect sizes. Similarly, continuous models, which are analogous to regression models, examine whether study characteristics that are assessed on a continuous scale are related to the effect sizes. As with categorical models, some continuous models may be completely specified in the sense that the systematic variability in the effect sizes is explained by the study characteristic that is used as a predictor. Continuous models are least squares regressions, calculated with each effect size weighted by the reciprocal of its variance (sample size). For example, He and colleagues (1999) found that risk of coronary heart disease was greater to the extent that nonsmokers had greater exposure to passive

smoke. Goodness-of-fit statistics enable analysts to determine the extent to which categorical or continuous models, or mixtures of these models provide correct depictions of study outcomes.

As an alternative analysis to predicting effect sizes using categorical and continuous models, an analyst can attain homogeneity by identifying outlying values among the effect sizes and sequentially removing those effect sizes that reduce the homogeneity statistic by the largest amount (e.g., Hedges 1987). Studies yielding effect sizes identified as outliers can then be examined to determine whether they appear to differ methodologically from the other studies. Also, inspection of the percentage of effect sizes removed to attain homogeneity allows one to determine whether the effect sizes are homogeneous aside from the presence of relatively few aberrant values. Under such circumstances, the mean attained after removal of such outliers may better represent the distribution of effect sizes than the mean based on all the effect sizes. In general, the diagnosis of outliers should occur prior to calculating moderator analyses; this diagnosis may locate a value or two that are so discrepant from the other effect sizes that they would dramatically alter any models fitted to effect sizes. Under such circumstances, these outliers should be removed from subsequent phases of the data analysis. Alternatively, outliers can be examined following categorical or continuous models (e.g., finding those that deviate the most from the values predicted by the models).

TRENDS IN THE PRACTICE OF META-

ANALYSIS

Although the quality of meta-analyses has been quite variable, it is possible to state the features that compose a high-quality meta-analysis, including success in locating studies, explicitness of criteria for selecting studies, thoroughness and accuracy in coding moderators variables and other study characteristics, accuracy in effect size computations, and adherence to the assumptions of metaanalytic statistics. When meta-analyses meet such standards, it is difficult to disagree with Rosenthal’s conclusion (1994) that it is ‘‘hardly justified to review a quantitative literature in the pre-meta- analytic, prequantitative manner’’ (p. 131). Yet merely meeting these high standards does not

necessarily make a meta-analysis an important scientific contribution. One factor affecting scientific contribution is that the conclusions that a research synthesis is able to reach are limited by the quality of the data that are synthesized. Serious methodological faults that are endemic in a research literature may well handicap a synthesis, unless it is designed to shed light on the influence of these faults. Also, to be regarded as important, the review must address an interesting question. Moreover, unless the paper reporting a meta-analysis ‘‘tells a good story,’’ its full value may go unappreciated by readers. Although there are many paths to a good story, Sternberg’s recommendations to authors of reviews (1991) are instructive: Pick interesting questions, challenge conventional understandings if at all possible, take a unified perspective on the phenomenon, offer a clear takehome message, and write well. Thus, the practice of meta-analysis should not preclude incorporating aspects of narrative reviewing, but instead should strive to incorporate and document the richness of the literature.

One reason that the quality of published syntheses has been quite variable is that it is a relatively new tool among scholars who practice it. Yet, as the methods of quantitative synthesis have become more sophisticated and widely disseminated, typical published meta-analyses have improved. At their best, meta-analyses advance knowledge about a phenomenon by explicating its typical patterns and showing when it is larger or smaller, negative or positive, and by testing theories about the phenomenon (see Miller and Pollock 1994). Meta-analysis should foster a healthy interaction between primary research and research synthesis, at once summarizing old research and suggesting promising directions for new research. One misperception that scholars sometimes express is that a meta-analysis represents a dead end for a literature, a point beyond which nothing more needs to be known. In contrast, carefully conducted meta-analyses can often be the best medicine for a literature, by documenting the robustness with which certain associations are attained, resulting in a sturdier foundation on which future theories may rest. In addition, meta-analyses can show where knowledge is at its thinnest, to help plan additional, primary-level research (see Eagly and Wood 1994). As a consequence of a carefully conducted meta-analysis, primary-level studies can

be designed with the complete literature in mind and will therefore have a better chance of contributing new knowledge. In this fashion, scientific resources can be directed most efficiently toward gains in knowledge. As time passes and new studies continue to accrue rapidly, it is likely that social scientists will rely more on quantitative syntheses to inform them about the knowledge that has accumulated in their research. Although it is possible that meta-analysis will become the purview of an elite class of researchers who specialize in research integration, as Schmidt (1992) argued, it seems more likely that meta-analysis will become a routine part of graduate training in many fields, enabling students to develop the skills necessary to ply the art and science of meta-analysis and to integrate findings across studies as a normal and routine part of their research activities.

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———, and W. Wood 1994 ‘‘Using Research Syntheses to Plan Future Research.’’ Pp. 485–500 in H. Cooper and L. V. Hedges, eds., The Handbook of Research Synthesis. New York: Russell Sage.

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———1991 Meta-Analytic Procedures for Social Research, rev. ed. Beverly Hills, Calif.: Sage.

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B. T. JOHNSON

METATHEORY

Metatheory in sociology is a relatively new specialty that aims to describe existing sociological theory systematically, and also, to some degree, to prescribe what future sociological theories ought to be like. It leaves to other specialties—most notably the sociology and history of sociology and the logic of theory construction—the problems of explaining and predicting how such theories have been, and can be, formulated.

There are two broad varieties of metatheory. One variety, synthetic, classifies whole theories according to some overarching typology; the other variety, analytic, first dissects theories into their underlying constituents and then classifies these constituents into types.

Some typologies encountered in synthetic metatheory refer to the time periods when the theories were originated, for example, forerunner, classical, and contemporary (Timasheff and Theodorson 1976 and Eisenstadt 1976 provide examples). Some refer to the places where the theories were originated, for example, France, Germany, Italy, and the United States (Bottomore and Nisbet 1978 and Gurvitch and Moore 1945 provide examples). Some refer to the substantive themes of the theories, for example, structuralfunctional, evolutionist, conflict, and symbolic interactionist (Turner 1986 and Collins 1988 provide examples). Some refer to the ideologies supported by the theories, for example, pro-establish- ment and anti-establishment (Martindale 1979 provides an example). Some refer to various combinations of all the above differences (Wiley 1979 and Ritzer 1983 provide examples).

Analytic metatheory is divisible into two broad classes: one in which the constituents of theories are required to have empirical referents, either directly or indirectly, and another in which these constituents are required or permitted to have nonempirical referents. Thus, one sociologist claims our theory should be brought ‘‘closer to nonempirical

standards of objectivity’’ (Alexander 1982), while another claims ‘‘sense-based inter-subjective verification is indispensable [to sociology]’’ (Wallace 1983). (This difference in kind of analytic metatheory reflects an applicability of the synthetic-analytic distinction to metamethod in sociology: In the synthetic variety of metamethod, whole methods are characterized as empirical or nonempirical, positivistic or hermeneutical, experimental or participant-obser- vational, and so on. In the analytic variety, such methods are dissected into their underlying constituents, which are then classified as measurement, interpretation, speculation, comparison, test, generalization, specification, deduction, induction, and so on.)

Some types of underlying constituents encountered in empirical analytic metatheory are ‘‘control’’ (Gibbs 1989); ‘‘individual actors,’’ ‘‘corporate actors,’’ ‘‘interests,’’ and ‘‘rights’’ (Coleman 1990); ‘‘rational action,’’ ‘‘nonrational action,’’ ‘‘individualist order,’’ and ‘‘collectivist order’’ (Alexander 1982); ‘‘social and cultural structures,’’ ‘‘spatial and temporal regularities,’’ ‘‘instinct,’’ ‘‘enculture,’’ ‘‘physiology,’’ ‘‘nurture,’’ ‘‘demography,’’ ‘‘psychical contagion,’’ ‘‘ecology,’’ and ‘‘artifacts’’ (Wallace 1983, 1988); and general causal images like ‘‘convergence,’’ ‘‘amplification,’’ ‘‘fusion,’’ ‘‘fission,’’ ‘‘tension,’’ ‘‘cross-pressure,’’ ‘‘dialectic,’’ and ‘‘cybernetic’’ (Wallace 1983, 1988). Some types of underlying constituents encountered in nonempirical analytic metatheory have been called (so far, without further explication or specification), ‘‘moral implication,’’ ‘‘moral commitments,’’ and ‘‘moral preferences’’ (Alexander 1982).

Metatheory in general has been sweepingly condemned as a dead end leading only to the study of ‘‘the grounds of other people’s arguments rather than substantive problems’’ (Skocpol 1987), and as holding ‘‘little prospect for further developments and new insights’’ (Collins 1986). Against such characterizations, however, certain unique and indispensable contributions of both synthetic and analytic metatheory to sociology should not be overlooked.

Synthetic metatheory plays obviously central roles in descriptive classifications of sociological theory (e.g., textbooks and course outlines), but they are no less central to the sociology and history of sociology, where efforts to account for the rise and fall of schools, or perspectives, in sociological analysis require systematic conceptualization of

such groupings. The contributions of nonempirical analytic metatheory remain unclear (as mentioned, the kinds of ideological commitment and moral foundation to which it refers, and their consequences for sociological theory, have yet to be specified) and, therefore, will not be examined here. The contributions of empirical analytic metatheory will occupy the rest of this article.

THREE CONTRIBUTIONS OF EMPIRICAL

ANALYTIC METATHEORY

Empirical analytic metatheory can aid (1) systematic cumulation of the end product of sociological investigation (namely, collectively validated empirical knowledge about social phenomena); (2) systematic construction of new versions of the principal means employed in generating that end product (namely, collectively shared theory and method); and (3) a sense of discipline-wide solidarity among sociologists of all theoretical traditions, all specializations and, eventually one hopes, among all social scientists.

Cumulation of Sociological Knowledge Knowledge can only cumulate when new knowledge of a given phenomenon is added to old knowledge of that same phenomenon (or, rather, insofar as no phenomenon is ever repeated exactly, that same type of phenomenon). The key to holding such objects of investigation constant is, of course, communication. That is to say, only the communication to investigator B of the identity of the exact phenomenon investigator A has examined, together with the exact results of that examination, can enable investigator B systematically to add new knowledge to A’s knowledge.

Disciplinary Communication Now it may be imagined that we already possess such communication in sociology, but we do not. Consider the terms social structure and culture. One can hardly doubt that, by denoting the substantive heart of our discipline, they indicate what the entire sociological enterprise is about. By virtually all accounts, however, each term signifies very different kinds of phenomena to different sociologists.

Thus, social structure has been authoritatively said, at various times for over two decades, to be ‘‘so fundamental to social science as to render its uncontested definition virtually impossible’’ (Udy 1968); to attract ‘‘little agreement on its empirical

referents’’ (Warriner 1981); and to possess a meaning that ‘‘remains unclear’’ (Turner 1986). ‘‘Few words,’’ it has been said, ‘‘do sociologists use more often than ‘structure,’ especially in the phrase ‘social structure.’ Yet we seldom ask what we mean by the word’’ (Homans 1975). In a more detailed statement, one analyst asserts that

The concept of social structure is used widely in sociology, often broadly, and with a variety of meanings. It may refer to social

differentiation, relations of production, forms of association, value integration, functional interdependence, statuses and roles, institutions, or combinations of these and other factors.

(Blau 1975)

Indeed, we can still read that ‘‘sociologists use the term [’social structure’] in diverse ways, each of which is either so vague as to preclude empirical application or so broad as to include virtually all collective features of human behavior’’ (Gibbs 1989). As recent evidence of this diversity, it is noteworthy that, where one sociologist claims that ‘‘for sociologists, the units of social structure are conceived of . . . as relational characteristics’’ (Smelser 1988), another refers, without explanation, to a type of ‘‘social structure’’ in which the participants ‘‘have no relations’’ (Coleman 1990).

The situation is no different with the term culture. Some years ago it was said that ‘‘by now just about everything has been thrown into ‘culture’ but the kitchen sink,’’ and the author of this remark then reflected that ‘‘The kitchen sink has been thrown in too’’ as part of ‘‘material culture’’ (Schneider 1973). Years later, it has again been pointed out that ‘‘Theorists of culture remain sorely divided on how best to define culture’’ (Wuthnow et al. 1984) and ‘‘values, orientations, customs, language, norms, [and religion]’’ have been referred to as though they were all somehow different from ‘‘culture’’ (Coleman 1990). No wonder at least one sociologist has simply given up: ‘‘[A]ny definition’’ of culture, he claims, ‘‘will be

(1) inclusive to the point of being meaningless, (2) arbitrary in the extreme, or (3) so vague as to promise only negligible empirical applicability’’ (Gibbs 1990).

More recently still, Gilmore affirms that ‘‘there is no current, widely accepted, composite resolution of the definition of culture,’’ and claims that as a result ‘‘the contemporary concept of culture

in sociology does not exclude any particular forms of [collective] activity.’’ This difficulty notwithstanding, there has arisen, Gilmore says, ‘‘a new appreciation of the salience of culture as an explanatory perspective in contemporary sociological research’’ (1992). To the extent that these judgments are true, one can only wonder what contribution an explanatory perspective that lacks even a rudimentary and tentative definition of its own central variable (and which expresses a kitch- en-sink inclusiveness that ‘‘does not exclude any particular empirical forms of activity’’) can possibly make to social science.

Regarding social structure, Rytina asserts his conviction that ‘‘Social structure is a general term for any collective social circumstance that is unalterable and given for the individual’’ and that such social structure ‘‘is the same for all and is beyond the capacity for alteration by any individual will’’ (1992). Apart from noticing, again, the kitchensink inclusiveness of this claim (‘‘any collective social circumstance’’), one wonders what good can come of conceptualizing social structure in a way that rules out the possibility of variable individual power (i.e., ‘‘the probability that one actor within a social relationship will be in a position to carry out his own will’’ [Weber 1978]). See, however, Sewell (1992) for explicit inclusion of ‘‘power’’ in struc- ture’’—although Sewell lumps ‘‘resources’’ and ‘‘schemas’’ (i.e., what others would distinguish as components of social structure and culture, respectively) together into a single undifferentiated ‘‘structure’’ concept.

Some other discussions of the ongoing social structure versus culture problem may be found in Emirbayer and Goodwin (1994), Hays (1994), Holmwood and Stewart (1994), Wallace (1986), and Whitmeyer (1994). It will also be noticed that in addition to ‘‘social structure’’ and ‘‘culture’’ the concept ‘‘agency’’ appears in some of these discussions, and a brief comment on it may be useful. Human ‘‘agency’’ is said, by Sewell, to refer to ‘‘the efficacy of human action,’’ and to arise from the actor’s ‘‘ability to apply [known schemas] to new contexts’’ and to act ‘‘creatively’’ (1992, pp. 2, 20). It is not easy to understand, however, why a special anthropocentric term is needed for such a phenomenon inasmuch as all action, by whatever agent, is (by any physical definition of ‘‘action’’) efficacious, and all ‘‘applications,’’ by definition, occur in ‘‘new’’ contexts and are thus ‘‘creative.’’

In response to such expressions of disciplinary decline (and acknowledging their strong evidential basis), empirical analytic metatheory falls back on Durkheim’s argument that insofar as ‘‘Every scientific investigation concerns a specific group of phenomena which are subsumed under the same definition,’’ it follows that ‘‘[the] sociologist’s first step must . . . be to define the things he treats so that we may know—he as well—exactly what his subject matter is. This is the prime and absolutely indispensable condition of any proof or verification’’ (1982).

Empirical analytic metatheory, then, seeks a common disciplinary language for sociologists everywhere, regardless of their specializations. Its proponents believe that only with the adoption of some such language can our discipline begin solving its central problems, namely, systematic knowledge cumulation, theory innovation, and solidarity enhancement.

(SEE ALSO: Epistemology; Scientific Explanation)

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MEXICAN STUDIES

Mexican history since the country achieved its independence from Spain in 1821 is marked by a set of dramatic events that created the context for fundamental social and economic changes. These events shaped contemporary Mexican society and established much of the current agenda of Mexican social and political studies. Three issues in particular have long historical antecedents. These are the ethnic question, the role of the state in development, and relations with the United States. Despite these continuities, social trends and preoccupations in Mexico have also differed according to historical period. In order to handle both

continuity and change, we will organize the discussion in terms of four main periods, each initiated by major events, and will consider the dominant trends and intellectual orientations of each period. The time between Mexican independence and the Mexican-American War, the first period is marked by economic stagnation and political fragmentation. The second period lasts from the aftermath of the Mexican-American War until the Mexican Revolution of 1910. Rapid but uneven economic development and political unification distinguish the second period. The third period begins with the consolidation of the Mexican Revolution and goes through the 1920s and on into the debt crises of the early 1980s. Nationalism, political centralization, and high rates of urbanization and industrialization characterize this period. Finally, we consider the two last decades of the twentieth century, shaped by the external opening of the economy with its accompanying economic and political liberalization.

This historical context and the unevenness of Mexico’s development make U.S.-Mexican relations different, in significant respects, from relations between other neighboring countries. The U.S.-Mexican border is the only international frontier that divides a developing country and a highly developed country. The contradictory trends of Mexico’s development shape U.S.-Mexican relations (Weintraub 1990). The two populations have been brought closer to each other in terms of trade, tourism, labor migration, and consumer aspirations. This increasing proximity can also create social distance as each population develops opposing images of the other. These are often based on the misunderstandings that result from wide disparities in income, standards of living, and political and family culture (Pastor and Castañeda 1988). For many Mexicans, the history of conflictive relations with the United States continues to negatively color perceptions of U.S. political and economic intentions toward Mexico.

Independence from Spain left Mexico an impoverished and fragmented nation. The main sources of external revenue—mining and specialized plantation agriculture—declined substantially. Internal markets were not strongly developed and were mainly concentrated in a few major cities. Thus, neither internal nor external trade provided enough stimuli to expand local agricultural or

industrial production. The economy was organized on a local and regional basis rather than on a national one. Within this context, politics was dominated by a decentralized system of caudillos (regional leaders, often military) and cacíques (local bosses and power brokers). The formal government alternated between a centralist and a federalist republic, after the short-lived Empire of Iturbide. The proponents of a centralist republic tended to be conservatives, supporting the maintenance of corporatist institutions such as the church, the army, the guilds, and the indigenous communities. In a sociological account of the processes shaping the Independence movement, the intellectual leader of the conservatives, Lucas Alamán ([1847] 1942), advocated a strong central power, economic protectíonism, the remedying of class inequality, and populating the empty spaces to the north through European Catholic colonization. In contrast, the federalists tended to be economically and politically liberal, arguing for individual property rights, free markets, and individual civil and political equality. The radical liberal parliamentarian, José María Luis Mora, went so far as to argue for the complete incorporation of the indigenous population into the market as a means to remedy backwardness and poverty (Lira Gonzalez 1984). A leading liberal politician and intellectual, Lorenzo de Zavala, admired the United States and considered it a model to emulate. He also viewed favorably the colonization of the northern territories by Protestant colonists from the United States (Lira Gonzalez 1984). Later, Zavala became the first vice president of the independent Republic of Texas. In order to govern, both the federalists and centralists relied on the caudillo-cacíque power structure. Thus, the paradigmatic caudillo of this period, Santa Anna, was president several times, under both centralist and federalist banners.

The loss of half of the national territory, first in the Texas War of lndependence of 1835–1836 and then in the Mexican-American War of 1846– 1848, demonstrated dramatically the costs of Mexico’s political and economic fragmentation. The conservatives entrenched themselves further in their corporate and hierarchical beliefs, leading finally to the ill-fated, conservative-backed empire of Maximillian of Hapsburg (1864–1867). The aftermath of the Mexican-American war was perhaps more traumatic for the liberals. They saw themselves as betrayed by the United States, which

they had regarded as a friend and an ally in modernizing Mexico. Thereafter, particularly with the experiences of the French intervention, Mexican liberals, while supporting market and individual freedoms and the abolition of corporations, were to become the main proponents of a strong state and of nationalism in Mexico.

Beginning with Beníto Juarez (president, 1861– 1863 and 1867–1872), liberals were to dominate the politics of Mexico until the Mexican Revolution, even in the paradoxical guise of the dictator, Porfirio Díaz (president, 1877–1880, 1884–1911). In face of the difficulties of achieving spontaneous economic and social progress, liberalism was modified, however, in an authoritarian and positivist direction. A disciple of Comte, Gabino Barreda, reorganized the educational system of the country to ensure a uniform and centralized system (Zea 1974). Justo Sierra (1969 [1901–1903]), one of Díaz’s ministers, wrote a new version of Mexican history as a political evolution that needed a period in which political rights would be limited. He saw economic progress as depending on civic education, as well as individualizing property rights in agriculture, industrial modernization, foreign investment, and trade. Though corporate rights to land had been abolished under Juarez, Díaz made this effective, particularly for the indigenous communities. Railways were built and roads improved. Political control was centralized through a bureaucratic system of patronage that gave the central government a more effective control of state and local governments. For the first time in fifty years, Mexico experienced a long period of peace and stability.

The Díaz period was one of considerable economic expansion in Mexico, but the style of development resulted in a series of social and economic dislocations that were to contribute to the Mexican Revolution of 1910. Commercial haciendas expanded, depriving many peasants of access to land. The new economic opportunities and improvements in communication affected communities throughout Mexico, encouraging villagers to give up traditional livelihoods for wage labor in mines, plantations, or as sharecroppers. As dependence on the market grew, so too national and regional economic downturns caused increasing discontent and hardship. Advocates of progress, such as Andrés Molina Enríquez ([1909] 1978), one of the intellectual leaders of the Mexican

Revolution, denounced the economic inequities produced by land concentration. lnstead, he placed his hopes on the emerging mestízo middle class of medium-scale farmers, merchants, manufacturers, and professionals. With Molina Enriquez, there is a clear statement of the ethnic basis of social change. Both the European-origin upper class and the indigenous peasantry are seen as incapable of progress. He sees the mestízo as the crucial Mexican identity capable of achieving economic development and social equity. By the time of the Mexican Revolution, the indigenous population, defined in census terms by ‘‘race’’ and non–Spanish-language use, constituted nearly half the Mexican population.

In spite of political centralization, the economy remained regionalized during the Díaz regime. The Mexican Revolution was essentially a set of regional movements and leaders, that responded to the particular economic problems and possibilities that the Porfirian expansion brought to local economies. These regional contexts included the sugar economy of Morelos; the henequen economy of Yucatan; the sharecropping, ranching, and mining economy of Chihuahua and Coahuila; and the emerging commercial farming economy of Sonora (Knight 1986).

The years from after the Mexican Revolution until approximately 1980 transformed Mexico from a society in which three-quarters of the population was agricultural and lived in small villages, to one in which less than a quarter of the population worked in agriculture and most people lived in large cities. This transformation was shaped by two outcomes of the revolution. One was an agrarian reform that destroyed the hacíenda system, replacing it with small and medium-scale commercial farming and a system of social property (the ejido) that reinstated and, at times, extended the rights to land of peasant communities. In the first thirty years after the Revolution, Mexican peasant agriculture was sufficiently strong to feed the growing urban population and help the country’s industrialization.

The second major legacy of the revolution was the consolidation of a centralized, modern political system around the official party of the revolution, known as the PRI (Partido Revolucionario Institucional) since 1948. The PRI based its control on corporate affiliations by industrial and peasant