Current issues in causation research

This week's conference on Causality and Explanation in the Sciences in Ghent was an unusually good academic meeting (link). Participants gathered from all over Europe, as well as a few from North America, Australia, and South Africa, to debate the logic and substance of causal interpretations of the world. Among other things, it provided all participants with a very good sense of the ideas about causation that are generating the most discussion today.

A general perception that emerges from the gestalt of papers at the conference is that there are three large focus areas in current research on scientific causation. First, there is interest in specifying what causal assertions and concepts mean in scientific explanations. What are the logical, conceptual, and pragmatic issues associated with causal assertions and explanations?

Second, there is a large body of work focusing on the methods we can use to support causal inference in the sciences. Every field of science produces volumes of data about variables and events over time. What methods exist to permit inferences about causal relationships among the observed variables and entities? This includes causal modeling statistical methods, but also comparative methods deriving from Mill's methods of difference and similarity.

Third, there is a group of philosophers and scientists who are primarily interested in the ontology of causation in various parts of the sciences. How do various factors exercise causal powers in ecology, the social sciences, or complex systems? Researchers in these areas need provisional answers to questions raised by the first two groups, but their focus is on substantive causal processes rather than the logic of causal statements.

It is useful to inventory half a dozen approaches that were repeatedly cited. This survey is impressionistic but gives an idea of the current landscape.

The mechanisms approach. The idea that we can explicate causation through the idea of a mechanism has been rising in importance over the past twenty years. The idea here is that the fundamental causal concept is that of a mechanism through which X brings about or produces Y. This is argued to be key to causation from single-case studies to large statistical studies suggesting a causal relationship between two or more variables. Peter Hedstrom and other exponents of analytical sociology are recent voices for this approach for the social sciences, though expositions of this approach don't usually go into the level of detail expected by philosophers like Woodward and Cartwright. An important paper by Peter Machamer, Lindley Darden and Carl Craver, "Thinking about Mechanisms", sets the terms of current technical discussions; their view is referred to as the MDC theory. A common concern is that the approach hasn't been as clear as it should be about what precisely a mechanism is. James Mahoney made this criticism in 2001 in "Beyond Correlational Analysis" reviewing Charles Ragin, Fuzzy-Set Social Science and Peter Hedstrom and Richard Swedberg, Social Mechanisms: An Analytical Approach to Social Theory (link), and we still need a more generally recognized specification of the idea. (See an earlier post on this approach; link.)

The manipulability account. Jim Woodward is perhaps the leading exponent of the manipulability (or interventionist) account. He develops his views in detail in his recent book, Making Things Happen: A Theory of Causal Explanation. The view is an intuitively plausible one: causal claims have to do with judgments about how the world would be if we altered certain circumstances. If we observe that the concentration of sulphuric acid is increasing in the atmosphere, we might consider the increasing volume of H2SO4 released by coal power plants from 1960 to 1990. And we might speculate that there is a causal connection between these facts. A counterfactual causal statement holds that: If X (increasing emissions) had not occurred, then Y (increasing acid rain) would not have occurred. The manipulability theory adds this point: if we could remove X from the sequence, then we would alter the value of Y. And this in turn makes good sense of the ways in which we design controlled experiments.

Difference-making. Another strand of thinking about causation focuses on the explanations we are looking for when we ask about the cause of some outcome. Here philosophers note that there are vastly many conditions that are causally necessary for an event but do not count as being explanatory. Lee Harvey Oswald was alive when he fired his rifle in Dallas; but this doesn't play an explanatory role in the assassination of Kennedy. Crudely speaking, we want to know which causal factors were salient; which factors made a difference in the outcome. Michael Strevens provides a detailed and innovative explication of this set of intuitions in his recent book Depth: An Account of Scientific Explanation, where he introduces his theory of "Kairetic" explanation.

Contrastive analysis as a theory of explanation. When we seek an explanation of something, we generally have something specific in mind: why X rather than X'? And an explanation that keys off the wrong contrast will fail, even though its premises are correct. Bas van Fraassen (1980), The Scientific Image, is often cited in this context. A conference participant, Petri Ylikoski, develops a contrastive counterfactual theory in his dissertation (link). This body of work seeks to clarify pragmatic issues concerning explanation, including understanding and explanatory relevance. If we ask for an explanation for why X occurred, we are usually presupposing a question like this:

Why did X occur [rather than Y]?

• Why is John carrying his umbrella [rather than not]?
• Why is John carrying his umbrella [rather than his raincoat]?
• Why is John carrying his umbrella [rather than his assistant Harry]?

These all demand different answers:

• Because he expects rain;
• Because it is too warm for a raincoat;
• Because Harry is carrying three heavy suitcases.

Here is a much-cited review article by Nancy Cartwright on van Fraasen's work (link), and here is a discussion of contrastive explanation by Jonathan Schaffer (link).

Causal modeling theory. This topic refers to the large body of statistical theory devoted to identifying potential causal relationships among observable variables in a large data set. Hubert Blalock is a founder of this approach (Causal Inferences in Nonexperimental Research; 1964) with his statistical models for causal path analysis. (Here is a short account of the history of path analysis in genetics.) Judea Pearl has contributed a great deal to the method of structural equation modeling (SEM) in Causality: Models, Reasoning and Inference and elsewhere. Here is a handbook article in which he explains the method and its causal relevance (link). Pearl maintains a research blog on causality here. Granger causality is a specific technique for assessing causal relationships within time series data: X Granger-causes Y if variations in X and Y together do a better job of predicting Y than variations in Y by itself.

Prior foundations of philosophical theories of causation. Two older discussions of causality also received some notice in these papers: J. L. Mackie on INUS conditions and causal fields (The Cement of the Universe: A Study of Causation) and Wesley Salmon on the causal structure of the world (Scientific Explanation and the Causal Structure of the World).

Nancy Cartwright's "Causation: One Word, Many Things" provides a very good contemporary review of the varieties of approaches that are currently being taken to the idea of causation (link).

Much of the intellectual vitality of this group of philosophers is captured in the major work recently edited by Phyllis McKay Illari, Federica Russo, and John Williamson, Causality in the Sciences. The book contains a very wide range of disciplines and approaches in its treatment of the topic.

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Posted in: CAT_explanation,causal mechanism,causal reasoning

Causal realism for sociology

The subject of causal explanation in the social sciences has been a recurring thread here (thread). Here are some summary thoughts about social causation.

First, there is such a thing as social causation. Causal realism is a defensible position when it comes to the social world: there are real social relations among social factors (structures, institutions, groups, norms, and salient social characteristics like race or gender). We can give a rigorous interpretation to claims like "racial discrimination causes health disparities in the United States" or "rail networks cause changes in patterns of habitation".

Second, it is crucial to recognize that causal relations depend on the existence of real social-causal mechanisms linking cause to effect. Discovery of correlations among factors does not constitute the whole meaning of a causal statement. Rather, it is necessary to have a theory of the mechanisms and processes that give rise to the correlation. Moreover, it is defensible to attribute a causal relation to a pair of factors even in the absence of a correlation between them, if we can provide evidence supporting the claim that there are specific mechanisms connecting them. So mechanisms are more fundamental than regularities.

Third, there is a key intellectual obligation that goes along with postulating real social mechanisms: to provide an account of the ontology or substrate within which these mechanisms operate. This I have attempted to provide through the theory of methodological localism (post) -- the idea that the causal nexus of the social world is constituted by the behaviors of socially situated and socially constructed individuals. To put the claim in its extreme form, every social mechanism derives from facts about institutional context, the features of the social construction and development of individuals, and the factors governing purposive agency in specific sorts of settings. And different research programs target different aspects of this nexus.

Fourth, the discovery of social mechanisms often requires the formulation of mid-level theories and models of these mechanisms and processes -- for example, the theory of free-riders. By mid-level theory I mean essentially the same thing that Robert Merton meant to convey when he introduced the term: an account of the real social processes that take place above the level of isolated individual action but below the level of full theories of whole social systems. Marx's theory of capitalism illustrates the latter; Jevons's theory of the individual consumer ss a utility maximizer illustrates the former. Coase's theory of transaction costs is a good example of a mid-level theory (The Firm, the Market, and the Law): general enough to apply across a wide range of institutional settings, but modest enough in its claim of comprehensiveness to admit of careful empirical investigation. Significantly, the theory of transaction costs has spawned major new developments in the new institutionalism in sociology (Mary Brinton and Victor Nee, eds., The New Institutionalism in Sociology).

And finally, it is important to look at a variety of typical forms of sociological reasoning in detail, in order to see how the postulation and discovery of social mechanisms play into mainstream sociological research. Properly understood, there is no contradiction between the effort to use quantitative tools to chart the empirical outlines of a complex social reality, and the use of theory, comparison, case studies, process-tracing, and other research approaches aimed at uncovering the salient social mechanisms that hold this empirical reality together.

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Posted in: CAT_methodology,causal reasoning

The historian's task

What are the intellectual tasks that define the historian's work? In a sense, this question is best answered on the basis of a careful reading of some good historians. But it will be useful to offer several simple answers to this foundational question as a sort of conceptual map of the nature of historical knowing.

First, historians are interested in providing conceptualizations and factual descriptions of events and circumstances in the past. This effort is an answer to questions like these: “What happened? What was it like? What were some of the circumstances and happenings that took place during this period in the past?” Sometimes this means simply reconstructing a complicated story from scattered historical sources – for example, in constructing a narrative of the Spanish Civil War or attempting to sort out the series of events that culminated in the Detroit race riot / uprising of 1967. But sometimes it means engaging in substantial conceptual work in order to arrive at a vocabulary in terms of which to characterize “what happened.” Concerning the disorders of 1967 in Detroit: was this a riot or an uprising? How did participants and contemporaries think about it?

Second, historians often want to answer “why” questions: “Why did this event occur? What were the conditions and forces that brought it about?” This body of questions invites the historian to provide an explanation of the event or pattern he or she describes: the rise of fascism in Spain, the collapse of the Ottoman Empire, the great global financial crisis of 2008. And providing an explanation requires, most basically, an account of the causal mechanisms, background circumstances, and human choices that brought the outcome about. We explain an historical outcome when we identify the social causes, forces, and actions that brought it about, or made it more likely.

Third, and related to the previous point, historians are sometimes interested in answering a “how” question: “How did this outcome come to pass? What were the processes through which the outcome occurred?” How did the Prussian Army succeed in defeating the superior French Army in 1870? How did Truman manage to defeat Dewey in the 1948 US election? Here the pragmatic interest of the historian’s account derives from the antecedent unlikelihood of the event in question: how was this outcome possible? This too is an explanation; but it is an answer to a “how possible” question rather than a “why necessary” question.

Fourth, often historians are interested in piecing together the human meanings and intentions that underlie a given complex series of historical actions. They want to help the reader make sense of the historical events and actions, in terms of the thoughts, motives, and states of mind of the participants. For example: Why did Napoleon III carelessly provoke Prussia into war in 1870 (David Baguley, Napoleon III and His Regime: An Extravaganza)? Why has the Burmese junta dictatorship been so intransigent in its treatment of democracy activist Aung San Suu Kyi (Nicholas Farrelly, Burma's General Objectives)? Why did northern cities in the United States develop such profound patterns of racial segregation after World War II (Thomas Sugrue, The Origins of the Urban Crisis: Race and Inequality in Postwar Detroit)? Why did young men in the 1910s and 1920s prefer dangerous, noisy internal combustion automobiles to safe, quiet electric vehicles (Gijs Moms, The Electric Vehicle: Technology and Expectations in the Automobile Age)? Answers to questions like these require interpretation of actions, meanings, and intentions – of individual actors and of cultures that characterize whole populations. This aspect of historical thinking is “hermeneutic,” interpretive, and ethnographic.

And, of course, the historian faces an even more basic intellectual task: that of discovering and making sense of the archival information that exists about a given event or time in the past. Historical data do not speak for themselves; archives are incomplete, ambiguous, contradictory, and confusing. The historian needs to interpret individual pieces of evidence; and he/she needs to be able to somehow fit the mass of evidence into a coherent and truthful story. So complex events like the Spanish Civil War present the historian with an ocean of historical traces in repositories and archives all over the world; these collections sometimes reflect specific efforts at concealment by the powerful (for example, Franco's efforts to conceal all evidence of mass killings of Republicans after the end of fighting); and the historian's task is to find ways of using this body of evidence to discern some of the truth about the past.

The photo above gives a small glimpse of the challenges the historian faces. In order to interpret the photo as "a moment in the Spanish Civil War", the historian needs to provide a careful interpretation of its provenance and content. Who are these soldiers? Where is the fighting taking place? Was the photo staged? What, if anything, does it tell us about the social conflicts and military circumstances of the Civil War? How can it help the reader of history to come to a better understanding of the experience of civil war?

In short, historians conceptualize, describe, contextualize, explain, and interpret events and circumstances of the past. They sketch out ways of representing the complex activities and events of the past; they explain and interpret significant outcomes; and they base their findings on evidence in the present that bears upon facts about the past. Their accounts need to be grounded on the evidence of the available historical record; and their explanations and interpretations require that the historian arrive at hypotheses about social causes and cultural meanings. Historians can turn to the best available theories in the social and behavioral sciences to arrive at theories about causal mechanisms and human behavior; so historical statements depend ultimately upon factual inquiry and theoretical reasoning. Ultimately, the historian's task is to shed light on the what, why, and how of the past, based on inferences from the evidence of the present.

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Posted in: CAT_history,causal reasoning,history,verstehen

MacIntyre and Taylor on the human sciences

There is a conception of social explanation that provides a common starting point for quite a few theories and approaches in a range of the social sciences. I'll call it the "rational, material, structural" paradigm. It looks at the task of social science as the discovery of explanations of social outcomes; and it brings an intellectual framework of purposive rationality, material social factors, and social structures exercising causal influence on individuals as the foundation of social explanation. Rational choice theory, Marxian economics, historical sociology, and the new institutionalism can each be described in roughly these terms: show how a given set of outcomes are the result of purposive choices by individuals within a given set of material and structural circumstances. These approaches depend on a highly abstracted description of human agency, with little attention to deep and important differences in agency across social, cultural, and historical settings. "Agents like these, in structures like those, produce outcomes like these." This is a powerful and compelling approach; so it is all the more important to recognize that there are other possible starting points for the social sciences.

In fact, this approach to social explanation stands in broad opposition to another important approach, the interpretivist approach. On the interpretive approach, the task of the human sciences is to understand human activities, actions, and social formations as unique historical expressions of human meaning and intention. Individuals are unique, and there are profound differences of mentality across historical settings. This "hermeneutic" approach is not interested in discovering causes of social outcomes, but instead in piecing together an interpretation of the meanings of a social outcome or production. This contrast between causal explanation and hermeneutic interpretation ultimately constitutes a major divide between styles of social thinking. (Yvonne Sherratt provides a very fine introduction to this approach; Continental Philosophy of Social Science.) Max Ringer, one of Weber's most insightful intellectual biographers, places this break at the center of Weber's development in the early twentieth century (Max Weber's Methodology: The Unification of the Cultural and Social Sciences). (See earlier discussions of two strands of thought in the philosophy of social science; link, link, link.)

On this approach, all social action is framed by a meaningful social world. To understand, explain, or predict patterns of human behavior, we must first penetrate the social world of the individual in historical concreteness: the meanings he/she attributes to her environment (social and natural); the values and goals she possesses; the choices she perceives; and the way she interprets other individuals' social action. Only then will we be able to analyze, interpret, and explain her behavior. But now the individual's action is thickly described in terms of the meanings, values, assumptions, and interpretive principles she employs in her own understanding of her world.

Most of the arguments in support of interpretive approaches to the human sciences have come from the continental tradition -- Dilthey, Ricoeur, Gadamer, Habermas. So let's consider two philosophers who have made original contributions to the historicist and interpretivist side of the debate, within the Anglo-American tradition. Consider first Alasdair MacIntyre's discussion of the possibility of comparative theories of politics ("Is a science of comparative politics possible?" in Alan Ryan, ed., The Philosophy of Social Explanation). MacIntyre poses the problem in these terms: "I shall be solely interested in the project of a political science, of the formulation of cross cultural, law-like causal generalizations which may in turn be explained by theories" (172). And roughly, MacIntyre's answer is that a science of comparative politics is not possible, because actions, structures, and practices are not directly comparable across historical settings. The Fiat strike pictured above is similar in some ways to a strike against General Motors or Land Rover in different times and places; but the political cultures, symbolic understandings, and modes of behavior of Italian, American, and British auto workers are profoundly different.

MacIntyre places great emphasis on the densely interlinked quality of local concepts, social practices, norms, and self ascriptions, with the implication that each practice or attitude is inextricably dependent on an ensemble of practices, beliefs, norms, concepts, and the like that are culturally specific and, in their aggregate, unique. Thus MacIntyre holds that as simple a question as this: "Do Britons and Italians differ in the level of pride they take in civic institutions?" is unanswerable because of cultural differences in the concept of pride (172-73).

Hence we cannot hope to compare an Italian's attitude to his government's acts with an Englishman's in respect of the pride each takes; any comparison would have to begin from the different range of virtues and emotions incorporated in the different social institutions. Once again the project of comparing attitudes independently of institutions and practices encounters difficulties. (173-74)

These points pertain to difficulties in identifying political attitudes cross-culturally. Could it be said, though, that political institutions and practices are less problematic? MacIntyre argues that political institutions and practices are themselves very much dependent on local political attitudes, so it isn't possible to provide an a-historical specification of a set of practices and institutions:

It is an obvious truism that no institution or practice is what it is, or does what it does, independently of what anyone whatsoever thinks or feels about it. For institutions and practices are always partially, even if to differing degrees, constituted by what certain people think and feel about them. (174)

So interpretation is mandatory -- for institutions no less than for individual behavior. So MacIntyre's position is disjunctive. He writes:

My thesis . . . can now be stated distinctively: either such generalizations about institutions will necessarily lack the kind of confirmation they require or they will be consequences of true generalizations about human rationality and not part of a specifically political science. (178)

Now turn to Charles Taylor in another pivotal essay, "Interpretation and the sciences of man" (Philosophical Papers: Volume 2, Philosophy and the Human Sciences). Taylor's central point is that the subject matter of the human sciences -- human actions and social arrangements -- always require interpretation. It is necessary for the observer to attribute meaning and intention to the action -- features that cannot be directly observed. He asks whether there are "brute data" in the human sciences -- facts that are wholly observational and require no "interpretation" on the part of the scientist (19)? Taylor thinks not; and therefore the human sciences require interpretation from the most basic description of data to the fullest historical description.

To be a full human agent, to be a person or a self in the ordinary meaning, is to exist in a space defined by distinctions of worth. . . . My claim is that this is not just a contingent fact about human agents, but is essential to what we would understand and recognize as full, normal human agency. (3)

Thus, human behaviour seen as action of agents who desire and are moved, who have goals and aspirations, necessarily offers a purchase for descriptions in terms of meaning what I have called "experiential meaning". (27)

One way of putting Taylor's critique of "brute data" is the idea that human actions must be characterized intentionally (34 ff.) in terms of the intentions and self understanding of the agent and that such factors can only be interpreted, not directly observed.

My thesis amounts to an alternative statement of the main proposition of interpretive social science, that an adequate account of human action must make the agents more understandable. On this view, it cannot be a sufficient objective of social theory that it just predict . . . the actual pattern of social or historical events. . . . A satisfactory explanation must also make sense of the agents. (116)

Taylor's discussion of ethnocentricity is important, since it provides a way out of the hermeneutic circle. He believes it is possible to interpret the alien culture without simply covertly projecting our categories onto the alien; and this we do through meaningful conversation with the other (124-25). This is a point that seems to converge with Habermas's notion of communicative action (The Theory of Communicative Action, Volume 1: Reason and the Rationalization of Society).

It isn't entirely clear how radically Taylor intends his argument. Is it that all social science requires interpretation, or that interpretation is a legitimate method among several? Is there room for generalizations and theories within Taylor's interpretive philosophy of social science? What should social science look like on Taylor's approach? Will it offer explanations, generalizations, models; or will it be simply a collection of concrete hermeneutical readings of different societies? Does causation have a place in such a science? (He says more about the role of theory in "Neutrality in political science"; Philosophical Papers: Volume 2, Philosophy and the Human Sciences, 63.)

Both MacIntyre and Taylor are highlighting an important point: human actions reflect purposes, beliefs, emotions, meanings, and solidarities that cannot be directly observed. And human practices are composed of the actions and thoughts of individual human actors -- with exactly this range of hermeneutic possibilities and indeterminacies. So the explanation of human action and practice presupposes some level of interpretation. There is no formula, no universal key to human agency, that permits us to "code" human behavior without the trouble of interpretation.

This said, I would still judge that the "rational, material, structural" paradigm with which we began has plenty of scope for application. For some purposes and in many historical settings, it is possible to describe the actor's state of mind in more abstract terms: he/she cares about X, Y, Z; she believes A, B, C; and she reasons that W is a good way of achieving a satisfactory level of attainment of the goods she aims at. In other words, purposive agency, within an account of the opportunities and constraints that surround action, provides a versatile basis for social action. And this is enough for much of political science, Marxist materialism, and the new institutionalism.

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Posted in: CAT_methodology,causal reasoning,comparative method,rationality,verstehen

Many small causes

When large historical events occur, we often want to know the causes that brought them about. And we often look at the world as if these causes too ought to be large, identifiable historical factors or forces. Big outcomes ought to have big, simple causes.

But what if sometimes the historical reality is significantly different from this picture? What if the causes of some "world-historical events" are themselves small, granular, gradual, and cumulative? What if there is no satisfyingly simple and macro answer to the question, why did Rome fall? Or why did the American civil war take the course it did? Or why did North Africa not develop a major Mediterranean economy and trading system? What if, instead, the best we can do in some of these cases is to identify a swarm of independent, small-scale processes and contingencies that eventually produced the outcome?

Take the fall of Rome. I suppose it is possible that the collapse of the empire resulted from a myriad of very different contingencies and organizational features in different parts of the empire: say, logistical difficulties in supplying armies in the German winter, particularly stubborn local resistance in Palestine, administrative decay in Roman Britain, population pressure in Egypt, and a particularly inept series of commanders in Gaul. Too many moving pieces, too much entropy, and some bad luck in personnel decisions, and administrative and military collapse ensues. Alaric sits in Rome.

What an account like this decidedly lacks, is a story about a few key systemic or environmental factors that made collapse "inevitable". Instead, the account is a dense survey of dozens or hundreds of small factors, separated in time and place, whose cumulative but contingent effect was the observed collapse of Rome. No simple necessity here -- "Rome collapsed because of fatal flaw X or environmental pressure Y" -- but instead a careful, granulated assessment of many small and solvable factors.

But here is a different possible historical account of the fall of Rome. An empire depends upon a few key organizational systems: a system of taxation, a system of effective far-flung military power, and a system of local administration in the various parts of the empire. We can take it as a given that the locals will resent imperial taxation, military presence, and governance. So there is a constant pressure against imperial institutions at each locus -- fiscal, military, and administrative. In order to maintain its grip on imperial power, Rome needed to continually support and revitalize its core functions. If taxation capacity slips, the other functions erode as well; but slippage in military capacity in turn undermines the other two functions. And now we're ready for a satisfyingly simple and systemic explanation of the fall of Rome: there was a gradual erosion of administrative competence that led to increasingly devastating failures in the central functions of taxation, military control, and local administration. Eventually this permitted catastrophic military failure in response to a fairly routine challenge. Administrative decline caused the fall of Rome.

I don't know whether either of these stories -- the "many small causes" story or the "systemic administrative failure" story -- is historically credible. But either could be historically accurate. And this is enough to establish the central point: we should not presuppose what the eventual historical explanation will look like.

I suppose there is no reason to expect apriori that large events will conform to either model. It may be that some great events do in fact result from a small number of large causes, while others do not. So the point here is one about the need to expand our historical imaginations, and not to permit our quest for simplicity and generality to obscure the possibility of complexity, granularity, and specificity when it comes to historical causation.

(Christopher Kelly's The Roman Empire: A Very Short Introduction is a very readable treatment of Rome's functioning as an empire. Kelly hands off the ball to Gibbon when it comes to explaining the fall of Rome, however (History of the Decline and Fall of the Roman Empire -- as Kelly says, decidedly not a "short history"). Michael Mann's The Sources of Social Power: Volume 1, A History of Power from the Beginning to AD 1760 gives something of the flavor of my "administrative decline" musing above. Likewise, the style of reasoning about revenues and coercion is very sympathetic to Charles Tilly's arguments about a somewhat later period in Coercion, Capital and European States: AD 990 - 1992.)

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Posted in: CAT_history,causal mechanism,causal reasoning,logistics,organization

Subsistence ethic as a causal factor

In his pathbreaking 1976 book, The Moral Economy of the Peasant: Rebellion and Subsistence in Southeast Asia, James Scott offers an explanation of popular politics based on the idea of a broadly shared "subsistence ethic" among the underclass people of Vietnam and Malaysia. Earlier postings (hidden transcripts, moral economy) have discussed several aspects of Scott's contributions. Here I want to focus on the causal argument that Scott offers, linking the subsistence ethic to the occurrence of rebellion.

Scott's view is that the ensemble of values and meanings current in a society have causal consequences for aggregate facts about the forms of political behavior that arise in that society. Speaking of the peasant rebellions in Southeast Asia of the 1930s Scott writes,

We can learn a great deal from [peasant] rebels who were defeated nearly a half-century ago. If we understand the indignation and rage which prompted them to risk everything, we can grasp what I have chosen to call their moral economy: their notion of economic justice and their working definition of exploitation--their view of which claims on their product were tolerable and which intolerable. Insofar as their moral economy is representative of peasants elsewhere, and I believe I can show that it is, we may move toward a fuller appreciation of the normative roots of peasant politics. If we understand, further, how the central economic and political transformations of the colonial era served to systematically violate the peasantry's vision of social equity, we may realize how a class "of low classness" came to provide . . . the shock troops of rebellion and revolution. (Scott 1976:3-4)

This passage represents a complex explanatory hypothesis about the sources of rebellion. Scott holds, first, that peasant rebels in Indochina in the 1930s shared the main outlines of a sense of justice and exploitation. This is a system of moral values concerning the distribution of material assets between participants (landlord, state, peasant, landless laborer) and the use of power and authority over the peasant. Second, this passage supposes that the values embodied in this sense of justice are motivationally effective: when the landlord or the state enacts policies which seriously offend this sense of justice, the peasant is angered and indignant, and motivated to take action against the offending party. Offense to his sense of justice affects the peasant's actions. Third, Scott asserts that this individual motivational factor aggregates over the peasantry as a whole to a collective disposition toward resistance and rebellion; that is, sufficient numbers of peasants were motivated by this sense of indignation and anger to engage in overt resistance. On this account, then, the subsistence ethic--its right of a subsistence floor and the expectations of reciprocity which it engenders--is a causal antecedent of rebellion. It is a factor whose presence and characteristics may be empirically investigated and which enhances the likelihood of various social events through identifiable mechanisms.

The subsistence ethic may be described quite simply. Scott writes, "we can begin, I believe, with two moral principles that seem firmly embedded in both the social patterns and injunctions of peasant life: the norm of reciprocity and the right to subsistence" (167). Villagers have a moral obligation to participate in traditional practices of reciprocity--labor sharing, contributions to disadvantaged kinsmen or fellow villagers, etc. And village institutions and elites alike have an obligation to respect the right of subsistence of poor villagers.

Claims on peasant incomes . . . were never legitimate when they infringed on what was judged to be the minimal culturally defined subsistence level; and second, the product of the land should be distributed in such a way that all were defined a subsistence niche. (10)

Thus the subsistence ethic functions as a sense of justice--a standard by which peasants evaluate the institutions and persons that constitute their social universe. The subsistence ethic thus constitutes a central component of the normative base which regulates relations among villagers in that it motivates and constrains peasant behavior. And the causal hypothesis is this: Changes in traditional practices and institutions which offend the subsistence ethic will make peasants more likely to resist or rebel. Rebellion is not a simple function of material deprivation, but rather a function of the values and expectations in terms of which the lower class group understands the changes which are imposed upon it.

We can identify a fairly complex chain of causal reasoning in Scott's account. First, the subsistence ethic is a standing condition in peasant society with causal consequences. It is embodied in current moral psychologies of members of the group and in the existing institutions of moral training through which new members are brought to share these values. Through the workings of social psychology this ethic leads individuals to possess certain dispositions to behave. The features and strength of this systems of values are relatively objective facts about a given society. In particular, it is possible to investigate the details of this ethic through a variety of empirical means: interviews with participants, observation of individual behavior, or analysis of the content of the institutions of moral training. Call this ensemble of institutions and current moral psychologies the "embodied social morality" (ESM).

In line with the idea that the subsistence ethic is a standing causal condition, Scott notes that the effectiveness of shared values varies substantially over different types of peasant communities. "The social strength of this ethic . . . varied from village to village and from region to region. It was strongest in areas where traditional village forms were well developed and not shattered by colonialism--Tonkin, Annam, Java, Upper Burma--and weakest in more recently settled pioneer areas like Lower Burma and Cochinchina" (Scott 1976:40). Moreover, these variations led to significant differences in the capacity of affected communities to achieve effective collective resistance. "Communitarian structures not only receive shocks more uniformly but they also have, due to their traditional solidarity, a greater capacity for collective action. . . . Thus, the argument runs, the more communal the village structure, the easier it is for a village to collectively defend its interests" (202).

We may now formulate Scott's causal thesis fairly clearly. The embodied social morality (ESM) is a standing condition within any society. This condition is causally related to collective dispositions to rebellion in such a way as to support the following judgments: (1) If the norms embodied in the ESM were suitably altered, the collective disposition to rebellion would be sharply diminished. (That is, the ESM is a necessary condition for the occurrence of rebellion in a suitable limited range of social situations.) (2) The presence of the ESM in conjunction with (a) unfavorable changes in the economic structure, (b) low level of inhibiting factors, and (c) appropriate stimulating conditions amount to a (virtually) sufficient condition for the occurrence of widespread rebellious behavior. (That is, the ESM is part of a set of jointly sufficient conditions for the occurrence of rebellion.) (3) It is possible to describe the causal mechanisms through which the ESM influences the occurrence of rebellious dispositions. These mechanisms depend upon (a) a model of individual motivation and action through which embodied norms influence individual behavior, and (b) a model of political processes through which individual behavioral dispositions aggregate to collective behavioral dispositions. (That is, the ESM is linked to its supposed causal consequences through appropriate sorts of mechanisms.)

What this account does not highlight -- and what is emphasized by several other theories we've discussed elsewhere (post, post, post, post) -- are the organizational features that underlie successful mobilization. Instead, Scott's account focuses on the motivational features that permit a group to be rallied to the risky business of rebellion.

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Posted in: CAT_collective action,causal reasoning,moral economy,norms,rebellion,social movements,Southeast Asia

Causal difference

Source: Federica Russo, Causality and Causal Modelling in the Social Sciences, p. 164

I've recently read a very interesting recent book by Federica Russo, Causality and Causal Modelling in the Social Sciences: Measuring Variations (Methodos Series) on the philosophical issues that arise in causal reasoning about social phenomena. Russo is obviously a talented and dedicated philosopher, and the book is a highly interesting contribution.

Explanation is at the center of scientific research, and explanation almost always involves the discovery of causal relations among factors, conditions, or events. This is true in the social sciences no less than in the natural sciences. But social causes look quite a bit different from causes of natural phenomena. They result from the choices and actions of numerous individuals rather than fixed natural laws, and the causal pathways that link antecedents to consequents are less exact than those linking gas leaks to explosions. Here as elsewhere, the foundational issues are different in the social sciences; so a central challenge for the philosophy of social science is to give a good, compelling account of causal reasoning about social phenomena that does justice to the research problems faced by social scientists. Federica Russo has done so in this book. The book focuses on probabilistic causation and causal modeling, and Russo offers a rigorous and accessible treatment of the full range of current debates. Her central goal is to shed more light on the methods of causal modeling, and she succeeds admirably in this ambition. Causality and Causal Modelling in the Social Sciences makes an important and original contribution.

Her approach to problems in the methodology and philosophy of social science is what she calls the “bottom-up” approach. She works from careful analysis of specific examples of social science reasoning about causation, and works upward to more general analytical findings about causal reasoning as it actually works in the hands of skilled social scientists. She uses five concrete case studies as a vehicle for teasing out the logic of causal inference that is at work: smoking and lung cancer, mother's education and child survival, health and wealth in a population, farmers' migration patterns, and factors causing job satisfaction. She looks at the causal arguments advanced in studies in each of these areas as a way of discovering some of the fundamental logical features of causal inference. The examples are drawn from a wider range of the social and behavioral sciences than is usually the case -- demography, public health, and migration, for example. Her insight is that we can learn a great deal about social science research by looking at good examples of empirical and theoretical reasoning about social changes. I think this is exactly right: it is much better to discover the problems that percolate out of the practice of social inquiry rather than imposing a framework of philosophical expectations onto social science practice.

Russo focuses her attention on the problem of explaining variation: what causes the variation of a certain characteristic over a population of individuals or events. This focus on “variation” rather than “regularity” is very convincing; it provides an appropriate and insightful alternative approach to framing problems for social science research and explanation. She offers a very adept discussion and interpretation of the meaning of causal statements and causal reasoning in the social sciences. The book provides a rigorous contribution to the large literature on the logic of quantitative reasoning about causes of population characteristics. Her case studies are well selected and well done. The book is founded on a deep and rigorous understanding of the most recent philosophical and methodological work on causal modeling.

The author does a very good job of positioning her understanding of the meaning of causal modeling and causal judgments in the social sciences. She honestly addresses the position of “causal realism” and the view that good explanations depend on discovering or hypothesizing causal mechanisms underlying the phenomena. Her chapter on causal mechanisms is a significant contribution to this growing debate within the philosophy of social science; she correctly observes that we need to have greater precision in our discussion of what a causal mechanism is supposed to be.

The book will be of substantial interest to the social scientists, psychologists, demographers, and philosophers who are interested in current debates about the mathematics and philosophy of causal inference. Social scientists and philosophers such as Skyrms, Cartwright, Woodward, Pearl, and Lieberson have developed a very deep set of controversies and debates about the proper interpretation of causal inference. Russo’s book is a substantial contribution to these debates and will engage much the same audiences.

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Posted in: CAT_mechanisms,causal reasoning

A range of causal questions

In considering important issues in the philosophy of the special sciences, I think it is always helpful to consider a variety of the kinds of intellectual challenges that arise in the area. This gives the philosopher something to work with -- not simply an apriori specification of an issue, but a nuanced set of examples.

So if we are interested in causal reasoning in the social sciences, we ought to pay attention to the kinds of causal questions that social scientists actually want to answer. Let's consider a range of causal questions that have arisen within historical and comparative sociology. In considering these examples, we should reflect on the types of analysis that would provide a satisfactory response to the question, and also the modes of research that would support an empirical response to the question.

• What causes ethnic violence (Horowitz 1985)?
• What caused ethnic violence in Rwanda?
• What caused twentieth-century revolutions (Wolf 1969)?
• What caused the Nicaraguan revolution?
• Why did revolution unfold as it did in the Canton Delta in 1911 (Hsieh 1974)?
• What factors enhance the likelihood of successful democratization (Przeworski 1991; Przeworski et al. 1996)?
• What causes urban residential segregation (Schelling 1978)?
• What causes political corruption (Klitgaard 1988)?
• What factors explain the success or failure of anti-corruption reforms (Klitgaard 1988)?
• What factors explain the East Asian economic miracle (Vogel 1991)?
• Why are there more violent crimes per 1000 in the US than Western Europe?
• Why was the political party of labor more successful in the UK than the US (Przeworski 1985)?
• Why is infant mortality significantly lower in Sri Lanka than Brazil or Egypt (Drèze and Sen 1989, 1995)?
• Why do millenarian cults occur in the post-colonial world (Adas 1979)?
• Why was agricultural technology stagnant in late imperial China (Elvin 1973)?
• Why are rural people more politically conservative than urban people?
• Why do social tastes and styles change as they do (Lieberson 2000)?
• Why did the name “Joshua” lose frequency in the United States in the 1990s (Lieberson 2000)?
• Why did the New England Patriots win the 2003 Super Bowl (Lieberson 1997)?
• Why did the political culture of corporations remain powerful among French workers in the 19th century (Sewell 1980)?
• Why did the heavy wheeled plough diffuse in the geographical pattern that it did in medieval France (Bloch 1966)?
• How did the socialist and republican parties of Spain mobilize the lower working class in support of their programs?
• How did the Solidarity Movement in Poland preserve its organization in face of state repression in the 1980s?
• Was the fact of skewed sex ratios in rural China a necessary condition for the occurrence of banditry and rebellion? Was this fact a contributing condition?
• Why was there no broad-based militant movement of the poor in the United States during the Great Depression?
• Why do restaurants commonly add a gratuity of 18% for parties of 6 or more?
  

We can learn a great deal about causal inquiry by reflecting briefly on a number of these examples. There is a common thread among these examples, in that each topic directs inquiry towards the question, “What are the causal conditions that give rise to a given social or historical outcome?” But there are a number of important differences among these examples as well. Some are about a category of outcome (“twentieth-century revolution” or “ethnic violence”), whereas others are about a historically specific outcome (the Nicaraguan revolution, the Rwandan genocide, the 2003 Super Bowl). Some are about large and publicly salient events, structures, and mentalities (states, revolutions, political cultures); others are about small-scale and unnoticed social characteristics (the frequency of first names). And there are numerous other nuances that emerge from consideration of these examples.

In each case it is a promising research strategy to attempt to discover the underlying social mechanisms that give rise to the outcome -- none of these examples suggests a purely statistical approach to the problem. So inquiry into the "microfoundations" of the causal relations that are uncovered is needed. And second, many of these examples suggest research approaches that make use of the methods of comparative historical sociology and case-study methodology. The techniques of "process-tracing" and small-N comparison of cases should help to arrive at empirically supportable theories of the causal relations that underlie these groups of phenomena.

References
Adas, Michael. 1979. Prophets of rebellion : millenarian protest movements against the European colonial order. Chapel Hill: University of North Carolina Press.
Bloch, Marc Léopold Benjamin. 1966. French rural history; an essay on its basic characteristics. Berkeley,: University of California Press.
Drèze, Jean, and Amartya Kumar Sen. 1989. Hunger and public action. Oxford: Clarendon Press.
———. 1995. India, economic development and social opportunity. Delhi: Oxford University Press.
Elvin, Mark. 1973. The Pattern of the Chinese Past. Stanford: Stanford University Press.
Horowitz, Donald L. 1985. Ethnic Groups in Conflict. Berkeley, California: University of California Press.
Hsieh, Winston. 1974. Peasant Insurrection and the Marketing Hierarchy in the Canton Delta, 1911. In The Chinese City Between Two Worlds, edited by M. Elvin and G. W. Skinner.
Klitgaard, Robert E. 1988. Controlling corruption. Berkeley: University of California Press.
Lieberson, Stanley. 1997. Modeling Social Processes: Some Lessons from Sports. Sociological Forum 12 (1):11-35.
———. 2000. Matter of taste : how names, fashions, and culture change. New Haven, CT: Yale University Press.
Przeworski, Adam. 1985. Capitalism and Social Democracy. Cambridge: Cambridge University Press.
———. 1991. Democracy and the Market: Political and Economic Reforms in Eastern Europe and Latin America, Studies in Rationality and Social Change. Cambridge: Cambridge University Press.
Przeworski, Adam, Michael Alvarez, Jose Antonio Cheibub, and Fernando Limongi. 1996. What makes democracies endure? Journal of Democracy 7 (1).
Schelling, Thomas C. 1978. Micromotives and Macrobehavior. New York: Norton.
Sewell, William Hamilton. 1980. Work and revolution in France : the language of labor from the Old Regime to 1848. Cambridge ; New York: Cambridge University Press.
Vogel, Ezra F. 1991. The Four Little Dragons: The Spread of Industrialization in East Asia. Cambridge, MA: Harvard University Press.
Wolf, Eric R. 1969. Peasant Wars of the Twentieth Century. New York: Harper & Row.

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Posted in: CAT_mechanisms,causal mechanism,causal reasoning,microfoundations

Causing public opinion

It is interesting to consider what sorts of things cause shifts in public opinion about specific issues. This week's national election is one important example. But what about more focused issues -- for example, the many ballot initiatives that were considered in many states? To what extent can we discover whether there is a measurable effect on public opinion by the organized efforts of advocacy groups through advertising and other strategies for reaching the minds of voters?

In these cases we might imagine that voters have a prior set of attitudes towards the issue -- perhaps including a large number of "don't know/don't care" people. Then a set of advocates form to lobby the public pro and con. They mount campaigns to influence voters' opinions towards the option they prefer. And on the day of the election voters will indicate their approval -- often in ratios quite different from those that were measured in pre-campaign surveys. So something happened to change the composition of public opinion on the issue. The question here is whether it is possible to estimate the effects of various possible influencers.

This seems like potentially a very simple area of causal reasoning about social processes. The outcome variable is fairly observable through polling and the final election, and the interventions are also usually observable as well, both in timing and magnitude. So the world may present us with a series of interventions and outcomes that support fairly strong causal conclusions -- for example, "each time ad campaign X hits the airwaves in a given market, there is an observed uptick in support for the proposition." It is unlikely that the correlation occurred as a result of random variations in both terms; we have a theory of how advertising influences voters; and we conclude that "ad campaign X was a causal factor in shaping voter opinion in this time period." (It is even possible that X played a role in both segments of opinion, resulting in an up-tick in both yes and no responses. Then we might also judge that X was effective at polarizing voters -- not the effect the strategist would have aimed at.)

This is an example of singular causal reasoning, in that it has to do with one population, one issue, and a specific series of interventions. What would be needed in order to arrive at a conclusion with generic scope -- for example, "advertising along the lines of X is generally effective in increasing support for its issue"? The most straightforward argument to the generic conclusion would be a study of an extended set of cases with a variety of strategies in play. If we discover something like this -- "In 80% of cases where X is included in the mix it is observed to have a positive effect on opinion" -- then we would have inductive reason for accepting the generic causal claim as well. This is basic experimental reasoning.

Take a hypothetical issue -- a referendum on a proposal for changing the system the state uses for assessing business taxes. Suppose that a polling firm has done weekly polling on the question and has recorded "yes/no/no opinion" since October 2007. Suppose that two organizations emerged in December to advocate for and against the proposal; that each raised about $5 million; and that each included an advertising campaign in its strategy. Suppose further that the "no" campaign also included a well-organized effort at the parish level to persuade church members to vote against the measure on religious grounds and the "yes" campaign included a grassroots effort to get university students and staff to be supportive of the measure on pro-science and pro-economy grounds. And suppose each organization mounted a "new media" campaign using email lists and web comminication to make its case. Finally, suppose we have good timeline data about the occurrence and volume of media spots throughout the period of June through November.

This scenario involves three types of causes, a timeline representing the application of the interventions, and a timeline representing the effects. From this body of data can we arrive at estimates of the relative efficacy of the three treatments? And does this set if conclusions provide credible guidance for other campaigns over other issues in other places?

There is also the question of the efficacy of the implementation of the strategies. Take the ad campaigns. Whether a specific campaign succeeds in changing viewers' opinions depends on the content, message, and production quality. Does the message resonate with a target segment of voters? Does the production design stimulate emotions that will lead to the desired vote? So evaluating efficacy needs to be done across instances of media as well as across varieties of media. (This is the function of focus groups and snap polls -- to evaluate the effects of specific messages and production choices on real voters.)

(Here is a link to some information about the process leading up to a positive vote on the Michigan Stem Cell initiative this month. A good general introduction to the social psychological theories about the formation of attitudes and opinions is Stuart Oskamp and P. Wesley Schultz, Attitudes and Opinions.)

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Posted in: CAT_mechanisms,causal mechanism,causal reasoning,quantitative methods,voter behavior

Policy, treatment, and mechanism

Policies are selected in order to bring about some desired social outcome or to prevent an undesired one. Medical treatments are applied in order to cure a disease or to ameliorate its effects. In each case an intervention is performed in the belief that this intervention will causally interact with a larger system in such a way as to bring about the desired state. On the basis of a body of beliefs and theories, we judge that T in circumstances C will bring about O with some degree of likelihood. If we did not have such a belief, then there would be no rational basis for choosing to apply the treatment. "Try something, try anything" isn't exactly a rational basis for policy choice.

In other words, policies and treatments depend on the availability of bodies of knowledge about the causal structure of the domain we're interested in -- what sorts of factors cause or inhibit what sorts of outcomes. This means we need to have some knowledge of the mechanisms that are at work in this domain. And it also means that we need to have some degree of ability to predict some future states -- "If you give the patient an aspirin her fever will come down" or "If we inject $700 billion into the financial system the stock market will recover."

Predictions of this sort could be grounded in two different sorts of reasoning. They might be purely inductive: "Clinical studies demonstrate that administration of an aspirin has a 90% probability of reducing fever." Or they could be based on hypotheses about the mechanisms that are operative: "Fever is caused by C; aspirin reduces C in the bloodstream; therefore we should expect that aspirin reduces fever by reducing C." And ideally we would hope that both forms of reasoning are available -- causal expectations are born out by clinical evidence.

Implicitly this story assumes that the relevant causal systems are pretty simple -- that there are only a few causal pathways and that it is possible to isolate them through experimental studies. We can then insert our proposed interventions into the causal diagram and have reasonable confidence that we can anticipate their effects. The logic of clinical trials as a way of establishing efficacy depends on this assumption of causal simplicity and isolation.

But what if the domain we're concerned with isn't like that? Suppose instead that there are many causal factors and a high degree of causal interdependence among the factors. And suppose that we have only limited knowledge of the strength and form of these interdependencies. Is it possible to make rationally justified interventions within such a system?

This description comes pretty close to what are referred to as complex systems. And the most basic finding in the study of complex systems is the extreme difficulty of anticipating future system states. Small interventions or variations in boundary conditions produce massive variations in later system states. But this is bad news for policy makers who are hoping to "steer" a complex system towards a more desirable state. There are good analytical reasons for thinking that they will not be able to anticipate the nature or magnitude or even direction of the effects of the intervention.

The study of complex systems is a collection of areas of research in mathematics, economics, and biology that attempt to arrive at better ways of modeling and projecting the behavior of systems with these complex causal interdependencies. This is an exciting field of research at places like the Santa Fe Institute and the University of Michigan. One important tool that had been extensively developed is the theory of agent-based modeling -- essentially, the effort to derive system properties as the aggregate result of the activities of independent agents at the micro-level. And a fairly durable result has emerged: run a model of a complex system a thousand times and you will get a wide distribution of outcomes. This means that we need to think of complex systems as being highly contingent and path-dependent in their behavior. The effect of an intervention may be a wide distribution of future states.

So far the argument is located at a pretty high level of abstraction. Simple causal systems admit of intelligent policy intervention, whereas complex, chaotic systems may not. But the important question is more concrete: which kind of system are we facing when we consider social policy or disease? Are social systems and diseases examples of complex systems? Can social systems be sufficiently disaggregated into fairly durable subsystems that admit of discrete causal analysis and intelligent intervention? What about diseases such as solid tumors? Can we have confidence in interventions such as chemotherapy? And, in both realms, can the findings of complexity theory be helpful by providing mathematical means for working out the system effects of various possible interventions?

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Posted in: CAT_mechanisms,causal reasoning,complexity,mechanism,prediction

What causes college success?

This sounds like a simple question. It sounds as if it is asking for us to discover a set of factors that influence the level of performance of individuals within a population when they get to colleges and universities. And we might speculate that there is a small group of potentially relevant factors: antecedent cognitive ability, attitudes, and values; location within a set of social relations that enhance or impede successful educational performance; quality of educational resources provided in K-12. We might reason that a given individual's performance is affected by his/her ability and motivation; enhancing or inhibiting circumstances; quality of educational "treatment"; and chance events or circumstances (a lucky break, an inspiring grandfather). And by examining antecedent conditions and outcomes across a large population of people, we might expect to be able to assess the degree to which various hypothesized factors in fact lead to differences in the performance of sub-populations defined by these factors. This analysis should shed light on the question, "What factors cause differences in university success?".

Sorting this out sounds like a straightforward empirical question. Consider this hypothetical study. First, identify a cohort of high school seniors -- let's say, all the seniors in 2000 in metropolitan Boston. Suppose this is 5,000 people. (1) Measure a set of features of their situation during high school: high school performance, family situation, features of the school attended, socioeconomic status, family status, racial-ethnic status. (2) Measure a set of psychological characteristics for each individual: motivation, determination, aptitude for mathematics, ... And, (3), measure college success five years following high school graduation (GPA, credit hours completed, degree attained).

Let's say that each individual is coded for ABILITY (1, 2, 3); MOTIVATION (1, 2, 3); SOCIOECONOMIC STATUS (1, 2, 3); RACE (A, B, C); FAMILY STATUS (A, B); HIGH SCHOOL QUALITY (1, 2, 3); HIGH SCHOOL PERFORMANCE (1, 2, 3); and a factor representing one particular educational or curricular theory -- let's say, PEER COUNSELING (T,F). And let's say that outcomes are coded as DEGREE (NONE, ASSOCIATES, BACHELORS, MASTERS, PROFESSIONAL) and GPA (1, 2, 3).

Now follow these individuals for 10 years: What further education do they pursue? Do they complete post-secondary education? What is their performance in post-secondary education? What occupations and jobs do they get? What income do they achieve by age 30? How much unemployment have they experienced?

Finally, we will do some basic statistics on this data set: compute the incomes and schooling for various sub-categories; test for correlations between outcomes and antecedent conditions; etc. Are there differences in outcomes when we cross-tabulate by ABILITY or MOTIVATION? What about if we cross-tabulate by RACE or SES? This analysis may produce statements like these hypothetical findings:

• People who completed high school with high performance were 2.5 times as likely to complete a college degree as those with a low performance.
• People whose family income was in the top quintile were 5 times as likely to complete a college degree as those from families in the bottom quintile.
• The college completion rate for white students, Hispanic students, and African-American students were X, Y, and Z respectively.
• High school graduates from high schools with peer counseling programs were X percent more likely to complete a bachelor's degree.
  
• People living in single-parent households during high school had completion rates of X compared to Y for dual-parent households.

A study along these lines provides a first indication of how some of these social characteristics may be related to performance in college. If a factor is not causally related to the outcome, then the population possessing this factor should have the same performances as the population lacking this factor (the null hypothesis). So if we find that differences in family structure or performance in high school are associated with differences in college performance, then we can infer that these factors play some causal or structural role in the outcome.

However, these findings do not establish specific causal linkages among the factors. Take the hypothetical finding about family income: is this statistical discovery the result of this mechanism (greater family income provides more support for tutoring and academic support) or this mechanism (greater family income is associated with familial values that put strong emphasis on successful completion of university degree) or this mechanism (greater family income confers social advantages that make completion easier for affluent students)? In other words, the statistical discovery does not determine the nature of the causal relation between the antecedent condition and the outcome; it simply points the researcher towards investigating the concrete social mechanisms that might be at work here.

The example demonstrates an important lesson about social inquiry. Statistical study of a population can in fact point us towards some preliminary hypotheses about social causation. But these statistical discoveries are only the first step. In order to confidently assert causal relationships between things like income and race, to educational outcomes, we need to arrive at a nuanced analysis of the social relations and institutions through which these gross factors play into individual outcomes. We need to have an account of the mechanisms and processes through which the effects of concrete social settings characterized by differences in family structure, SES, race, or schools play out in the social psychology and educational opportunities that determine the ultimate outcomes of the young people who pass through them.

(A similar line of thought can be found in this posting on the problem of sorting out the data establishing correlations between race and asthma.)

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Posted in: CAT_mechanisms,causal reasoning,education,explanation