Causal diagrams and causal mechanisms

There is a long history of the use of directed causal diagrams to represent hypotheses about causation. Can the mathematics and graphical systems created for statistical causal modeling be adapted to represent and evaluate hypotheses about causal mechanisms and outcomes?

In the causal modeling literature the structure of a causal hypothesis is something like this: variable T increases/ decreases the probability of the occurrence of outcome E. This is the causal relevance criterion described by Wesley Salmon in Scientific Explanation and the Causal Structure of the World. It is a fundamentally statistical understanding of causality.

Here is a classic causal path model by Blau and Duncan indicating the relationships among a number of causal factors in bringing about an outcome of interest — “respondent’s first job”.

 

This construction aims at joining a qualitative hypothesis about the causal relations among a set of factors with a quantitative measurements of the correlations and conditional probabilities that support these causal relations. The whole construction often takes its origin in a multivariate regression model.

Aage Sørensen describes the underlying methodological premise of quantitative causal research in these terms in his contribution to Frontiers of Sociology (Annals of the International Institute of Sociology Vol. 11):

Understanding the association between observed variables is what most of us believe research is about. However, we rarely worry about the functional form of the relationship. The main reason is that we rarely worry about how we get from our ideas about how change is brought about, or the mechanisms of social processes, to empirical observation. In other words, sociologists rarely model mechanisms explicitly. In the few cases where they do model mechanisms, they are labeled mathematical sociologists, not a very large or important specialty in sociology. (370)

My question here is whether this scheme of representation of causal relationships and the graphical schemes that have developed around it are useful for the analytics of causal mechanisms.

The background metaphysics assumed in the causal modeling literature is Humean and “causal-factor” based; such-and-so factor increases the probability of occurrence of an outcome or an intermediate variable, the simultaneous occurrence of A and B increase the probability of the outcome, etc. Quoting Peter Hedstrom on causal modeling:

In the words of Lazarsfeld (1955: 124-5), “If we have a relationship between x and y; and if for any antecedent test factor the partial relationships between x and y do not disappear, then the original relationship should be called a causal one.” (

Dissecting the Social: On the Principles of Analytical Sociology

)

The current iteration of causal modeling is a directed acyclic graph (DAG). Felix Elwert provides an accessible introduction to directed acyclic graphs in his contribution to Handbook of Causal Analysis for Social Research (link). Here is a short description provided by Elwert:

DAGs are visual representations of qualitative causal assumptions: They encode researchers’ expert knowledge and beliefs about how the world works. Simple rules then map these causal assumptions onto statements about probability distributions: They reveal the structure of associations and independencies that could be observed if the data were generated according to the causal assumptions encoded in the DAG. This translation between causal assumptions and observable associations underlies the two primary uses for DAGs. First, DAGs can be used to prove or disprove the identification of causal effects, that is, the possibility of computing causal effects from observable data. Since identification is always conditional on the validity of the assumed causal model, it is fortunate that the second main use of DAGs is to present those assumptions explicitly and reveal their testable implications, if any. (246)

A DAG can be interpreted as a non-parametric structural equation model, according to Elwert. (Non-parametric here means simply that we do not assume that the data are distributed normally.) Elwert credits the development of the logic of DAGs to Judea Pearl and Peter Spirtes, along with other researchers within the causal modeling community.
 
Johannes Textor and a team of researchers have implemented DAGitty, a platform for creating and using DAGs in appropriate fields, including especially epidemiology (link). A crucial feature of DAGitty is that it is not solely a graphical program for drawing graphs of possible causal relationships; rather, it embodies an underlying logic which generates expected statistical relationships among variables given the stipulated relationships on the graph. Here is a screenshot from the platform:
 

 

 
 
The question to consider here is whether there is a relationship between the methodology of causal mechanisms and the causal theory reflected in these causal diagrams. 
 
It is apparent that the underlying ontological assumptions associated with the two approaches are quite different. Causal mechanisms theory is generally associated with a realist approach to the social world, and generally rejects the Humean theory of causation. The causal diagram approach, by contrast, is premised on the Humean and statistical approach to causation.  A causal mechanisms hypothesis is not fundamentally evaluated in terms of the statistical relationships among a set of variables; whereas a standard causal model is wholly intertwined with the mathematics of conditional correlation.
 
Consider a few examples. Here is a complex graphical representation of a process understood in terms of causal mechanisms from McGinnes and Elandy, “Unintended Behavioural Consequences of Publishing Performance Data: Is More Always Better?” (link):

 

Plainly this model is impossible to evaluate statistically by attempting to measure each of the variables; instead, the researchers proceed by validating the individual mechanisms identified here as well as the direction of influence they have on other intermediate outcomes. The outcome of interest is “quality of learning” at the center of the graph; and the diagram attempts to represent the complex structure of causal influences that exist among several dozen mechanisms or causal factors.

Here is another example of a causal mechanisms path diagram, this time representing the causal system involved in drought and mental health by Vins, Bell, Saha, and Hess (link).

 
 
Here too the model is not offered as a statistical representation of covariance among variables; rather, it is a hypothetical sketch of the factors which play in mechanisms leading from drought to depression and anxiety in a population. And the assessment of the model should not take the form of a statistical evaluation (a non-parametric structural equation model), but rather a piecemeal verification of the validity of the specific mechanisms cited. (John Gerring argues that this is a major weakness in causal mechanisms theory, however, in “Causal Mechanisms? Yes, But …” (link).)
 
It seems, therefore, that the superficial similarity between a causal model graph (a DAG) and a causal mechanisms diagram is only skin-deep. Fundamentally the two approaches make very different assumptions about both ontology (what a causal relationship is) and epistemology (how we should empirically evaluate a causal claim). So it seems unlikely that it will be fruitful for causal-mechanisms theorists to attempt to adapt methods like DAGs to represent the causal claims they want to advance and evaluate.
 
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Causal concepts

source: D. Little, “Causal Explanation in the Social Sciences,” Southern Journal of Philosophy (1995) (link)


It may be useful to provide a brief account of some of the key ideas that are often invoked in causal explanations in the social sciences. (Here is an earlier post that summarized some current issues in causation research; link. And here are several earlier articles on causal explanation; link, linklink.)

The general idea of a social cause (X causes Y) goes along these lines: X is a structure or feature of social life that varies across social settings and whose presence increases the likelihood of occurrence of Y. The presence of X (perhaps in the presence of Y and Z as well) contributes to processes leading to Y.

This simple formulation contains several hidden assumptions — most importantly, that outcomes have causes, that causes retain their characteristics over time and across instances, and that there are processes or dynamics within the domain of things and processes that convey with some form of necessity one set of circumstances and events onto another.

An example

For example, consider this hypothetical narrative describing a riot in a European city with a large community of impoverished immigrant people:

  • (C1) simmering resentment by immigrant youth of joblessness and low social esteem
  • (C2) heat wave creating discomfort and misery in crowded neighborhoods
  • (C3) chronic disrespectful and rough police treatment of immigrant youth
  • (I) forceful arrest of mis-identified young person in a city park, leading to serious injury of the youth
  • (O) several days of rioting occur
The associated causal hypothesis goes along these lines: In the context of simmering resentment by immigrant youth and a pattern of mistreatment by police, feelings in the community were unusually elevated by the heat wave. When the arrest occurred a small protest began in the park, which spread to other blocks in the city and eventuated in the burning of cars, smashing of shop windows, and multiple further arrests.

Conditions Ci are standing conditions that played a causal role in the occurrence of the riot. The arrest incident was the instigating event, the match that ignited the social “gasoline”. If any of C1, C2, C3 had been changed six months earlier, it is unlikely that O would have occurred. Each was necessary for I leading to O in the circumstances of the day.  If C1, C2, C3 are present, it is likely that some instigating event will occur in the normal hustle-bustle of urban life. I was the instigating condition. For researchers seeking general explanations of urban unrest, C1 and C3 appear to be strong candidates for common causes across many examples of urban riots. Two mechanisms are invoked here: a mechanism having to do with the individual’s propensity to engage in protest (“resentment and mistreatment elevates propensity to protest”) and a mechanism having to do with the spread of protest (“a small disturbance between a few teenagers and the police escalates through direct contact with other disaffected individuals through the neighborhood”).

Here are brief discussions of many of the concepts that are commonly invoked in discussions of social causation.

Causal narrative

An organized and temporally directed account of the occurrence of an event or change, identifying the conditions, circumstances, and events that were causally relevant to its occurrence. A narrative needs to provide empirical evidence for its empirical claims and theoretical justification for the causal mechanisms and processes it postulates.

Standing condition

A condition or circumstance that persists through an extended period of time and that serves as part of the necessary causal background of a given causal process or mechanism. Persistent racial isolation is a standing condition in many explanations of the effects of inner city poverty.

Instigating event

An instigating event is an occurrence, including change of state of some background property, that triggers a change in some other property or process. The early-morning arrest by patrons of a blind pig (unlicensed tavern) in Detroit was the instigating event of the 1967 Detroit riot/uprising.

Necessary condition

A condition that must be present in order for a given causal interaction to occur. “If X had not been present, the outcome O would not have occurred.”

Sufficient condition (conjunction of conditions)

A condition (or conjunction of conditions) whose presence suffices to bring about the outcome. “If X&Y&Z were present, then O would have occurred.”

Counterfactual statements

It is worth underlining the point that necessary and sufficient conditions invoke counterfactual statements: If X had not occurred, Y would not have occurred. The logic of counterfactuals (modal logic) has a controversial and unresolved history. But given that causal language always implies some kind of necessity, we cannot dispense with counterfactuals and still have an adequate causal vocabulary.

INUS condition (J. L. Mackie)

J.L. Mackie’s work on causation in The Cement of the Universe: A Study of Causation brought to closure a long line of thought about the logic of causal relations, culminating in his concept of INUS conditions. Consider this complex causal statement about the circumstances causing P:

‘All (ABC or DGH or JKL) are followed by P’ and ‘All P are preceded by (ABC or DGH or JKL)’ (Mackie, 62)

Mackie then defines an INUS condition:

Then in the case described above the complex formula ‘(ABC or DGH or JKL)’ represents a condition which is both necessary and sufficient for P: each conjunction, such as ‘ABC’, represents a condition which is sufficient but not necessary for P. Besides, ABC is a minimal sufficient condition:  none of its conjuncts is redundant: no part of it, such as AB, is itself sufficient for P. But each single factor, such as A, is neither a necessary nor a sufficient condition for P. Yet it is clearly related to P in an important way: it is an insufficient but non-redundant part of an unnecessary but sufficient condition: it will be convenient to call this … an inus condition. (62)

To simplify:

A is an INUS condition for P if for some X and Y, (AX v Y) is a necessary and sufficient condition for P, but A is not sufficient for P and X is not sufficient for P.

Causal mechanism

An interlocked series of events and processes that, once initiated by some set of conditions, [usually] brings about a given outcome O. The idea that there are real mechanisms embodied in the “stuff” of a given domain of phenomena provides a way of presenting causal relations that serves as a powerful alternative to the “regularity” view associated with Hume. “Poor performance on standardized tests by specific groups is caused by the mechanism of stereotype threat” (Claude Steele, Whistling Vivaldi: How Stereotypes Affect Us and What We Can Do (Issues of Our Time)). This mechanism is a hypothesized process within the cognitive-emotional system of the subjects of the test. (James Mahoney’s survey article on the mechanisms literature is a good introduction to the debate; link.)

Causal powers

The idea that certain kinds of things (metals, gases, military bureaucracies) have internal characteristics that lead them to interact causally with the world in specific and knowable ways. This means that we can sometimes identify dispositional properties that attach to kinds of things. Metals conduct electricity; gases expand when heated; military bureaucracies centralize command functions. (Harre and Madden, Causal Powers: Theory of Natural Necessity)

Probabilistic causal relation

A relationship between A and O such that the occurrence of A increases/decreases the likelihood of the occurrence of O. This can be stated in terms of conditional probabilities: P(O|A) ≠ P(O) [the probability of O given A is not equal to the probability of O]. For a causal realist, the definition is extended by a hypothesis about an underlying causal mechanism. [Smoking is a probabilistic cause of lung cancer [working through physiological mechanisms X,Y,Z]. This is equivalent to Wesley Salmon’s criterion of causal relevance (Scientific Explanation and the Causal Structure of the World).

Causal explanation of a singular event

When we are interested in the explanation of a single event, a causal narrative leading up to that event is generally what we are looking for. What led to the outbreak of World War I? Why did Khomeini come to power in Iran in 1979? There are generally two difficult problems facing a proposed causal-narrative explanation of a singular event. First, we need to somehow empirically validate the claims about causal mechanisms and processes that are invoked in the narrative. But since this is a singular event, we do not have the option of using experimental methods to empirically test the claim “X leads by mechanism M to Y” that the narrative proposes. This is one important reason why mechanism theorists have generally required that specified mechanisms have roughly similar causal properties in a range of circumstances. Circumstances embodying the core features of a public goods problem usually lead to elevated levels of free riding — whether in public radio fundraising, strikes, classroom discussions, or rebellions. Second, there is the problem of alternative realizability and multiple causal pathways leading to the same outcome. If the conditions leading to World War I were sufficiently ominous, then whether the assassination of the Archduke or some other event brought it about is of less explanatory importance. Given that potential instigating events occur with a certain probability, some event would have occurred within those few months that led to war. So it is better to identify the standing conditions that made war likely as the causes, rather than the assassination of the Archduke.

Generalizations about the causes of a kind of social entity or event

We are often interested in answering causal questions about classes of events: Why do peasant rebellions occur? Why does corruption rise to such high levels in many cities? Why do democracies not wage war against each other? Here we are looking for common conjunctions of causal factors that can be shown to be causally relevant in many such events. It is possible that we will discover that peasant rebellions do not have a single set of causal antecedents; rather there are multiple profiles of peasant rebellions, each with a set of causal conditions significantly different from the other profiles.

Methods of causal inquiry

How can social researchers identify causal relations among social events and structures? There are several groups of methods that social scientists and historians have employed: statistical-causal models, small-N models based on Mill’s methods of similarity and difference (link, link), and case studies and process-tracing methods through which researchers seek to identify and confirm causal relations in individual cases. In each case the method derives from fundamental ideas about the nature of causation: the idea that causal relations between several factors give rise to statistical regularities when we have a large number of cases; the idea that we can use the features of necessary and sufficient conditions to select cases in order to include or exclude certain factors as causally related to the outcome; and the idea that causal mechanisms and processes can often be observed fairly directly in the historical record (Alexander George and Andrew Bennett, Case Studies and Theory Development in the Social Sciences).

Causal inference and random trials

image: Tamil Nadu nutrition study

Nancy Cartwright has spent much of her career probing the assumptions scientists make about causation. She has helped to demonstrate that the Humean assumptions about causation that philosophers (including Carl Hempel) carried into twentieth century philosophy of science don’t come close to answering the question correctly, and she has provided many reasons to take seriously the ideas of causal powers and mechanisms rather than governing causal regularities. How the Laws of Physics Lie is an important contribution to the philosophy of science and to realist theory.

Her current book Evidence-Based Policy: A Practical Guide to Doing It Better (with Jeremy Hardie) provides a different critical perspective on causal inference, this time in the context of social policy reasoning. The design and implementation of public policies rest upon a fundamental premise: that we can have evidence-based reasons for predicting what the effects of the policy tool will likely be. But what kind of evidence might that be? The dominant form of evidence favored in the policy science field is random controlled trials: specify the policy intervention P, choose a domain of cases to apply the intervention P to, randomly select cases to receive the intervention (versus the control group that does not), and measure the value of the outcome of interest. If there is a significant difference in the value of the outcome between test group and control group, then we have evidence that P had an effect.

In a nutshell, C&H take issue with the conviction that random controlled trials  (RCT) — the gold standard of causal inference and experiment in clinical medicine — provide a basis for expecting that a given policy intervention will have similar effects in the future. Their book can be read as a critique of an excessively statistical understanding of social causality, without realistic analysis of the underlying mechanisms and processes. As Cartwright and Hardie state repeatedly, RCT evidence shows only that the policy worked on the circumstances tested in the study. Instead, they argue that we need to offer evidence about two additional considerations: whether the “causal principle” associated with P will remain the same in new circumstances; and whether the associated conditions necessary for the operation of this principle will be present in the new circumstances.

Here is a fundamental statement of what they mean by a causal principle:

We suppose that causes do not produce their effects by accident, at least not if you are to be able to make reliable predictions about what will happen if you intervene. Rather, if a cause produces an effect, it does so because there is a reliable, systematic connection between the two, a connection that is described in a causal principle. (22)

The statement, “El Nino causes wet winters in North America,” is a causal principle. But causal principles are neither universal nor exceptionless:

The fact that causal principles can differ from locale to locale means that you cannot read off that a policy will work here from even very solid evidence that it worked somewhere else. (23)

Here is a more extensive description of this idea:

Causal principles are not universal. They differ from place to place and from time to time. That means that it is not enough for you to know that the policy worked somewhere or even that it has worked at some time here. “It worked there”; it played a positive causal role there. So it was one of the factors from a causal principle that holds there. To predict that it will work here, you need to know that it is one of the factors from a causal principle that holds here. That is what ensures that it can play a positive causal role for you. (50)

Cartwright and Hardie look at causation along the lines of J. L. Mackie’s analysis of INUS conditions in The Cement of the Universe: a factor is a cause if it is an “Insufficient but Necessary part of an Unnecessary but Sufficient condition for producing a contribution to the effect” (23). The evidence of favorable CRT studies for a given policy intervention doesn’t show that this policy will work in the new circumstances of the new proposed application. In order to draw this inference we need to have confidence that the treatment will play the same causal role in the new setting, and that the necessary conditions will be present in that setting. In other words, we need a more detailed causal analysis of the past and the proposed future.

Here is a sketch of the argument that C&H suggest we need to provide in order to project favorable RCT studies onto future applications:

  1. x works there (i.e., x genuinely appears in the causal principle that governs the production of y there post-implementation). 
  2. Here and there share that causal principle post-implementation. 
  3. The support factors necessary for x to contribute under that principle are present for at least some individuals here post-implementation. 
  4. Conclusion. x works here (i.e., x genuinely appears in the causal principle that governs the production of y here post-implementation and the support factors necessary for it to contribute to y are present for at least some individuals here post-implementation). (41)

One way of offering support for premise 2 is to engage in the method of process tracing:

This method confirms the existence of a causal connection between start and finish by confirming, one-by-one, a series of smaller causal steps in between. (38)

Cartwright doesn’t put her case in these terms, but I would say that the heart of her intuition is that social outcomes are different from medical outcomes because of their inherent causal heterogeneity. In the social world outcomes like teen pregnancy rates or high school dropout rates are the result of a bundle of conjunctural causal processes. So projecting the results of past random controlled trials into the future requires that we first confirm that the same causal influences and important background conditions are at work. And this is rarely the case. So the fundamental underlying prescription is a pragmatic causal realism about social processes: in order to design and implement policies, we need to have a well developed map of the real causal processes and mechanisms that are underway in the production of the effect we would like to change. In other words, we need to be causal realists if we are to be effective policy makers.

(It is worth observing that this book is deliberately different in tone and specialization from Cartwright’s other monographs in the philosophy of causation. The book is designed to be useful for real practitioners of public policy, and it offers clear advice about how to gain the understandings needed in order to validate the idea that a given policy will have desired effects in a novel setting.)

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.

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.

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.

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.)

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.

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.

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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