Is history probabilistic?

Many of our intuitions about causality are driven by a background assumption of determinism: one cause, one effect, always. But it is evident in many realms -- including especially the social world -- that causation is probabilistic. A cause makes its effects more likely than they would be in the absence of the cause. Exposure to a Zika-infected mosquito makes it more likely that the individual will acquire the illness; but many people exposed to Zika mosquitoes do not develop the illness. Wesley Salmon formulated this idea in terms of the concept of causal relevance: C is causally relevant to O just in case the conditional probability of O given C is different from the probability of O. (Some causes reduce the probability of their outcomes.)

There is much more to say about this model -- chiefly the point that causes rarely exercise their powers in isolation from other factors. So, as J.L. Mackie worked out in The Cement of the Universe: A Study of Causation, we need to be looking for conjunctions of factors that jointly affect the probability of the occurrence of O. Causation is generally conjunctural. But the essential fact remains: no matter how many additional factors we add to the analysis, we are still unlikely to arrive at deterministic causal statements: "whenever ABCDE occurs, O always occurs."

But here is another kind of certainty that also arises in a probabilistic world. When sequences are governed by objective probabilities, we are uncertain about any single outcome. But we can be highly confident that a long series of trials will converge around the underlying probability. In an extended series of throws of a fair pair of dice the frequency of throwing a 7 will converge around 6/36, whereas the frequency of throwing a 12 will converge around 1/36. So we can be confident that the eventual set of outcomes will look like the histogram above.

Can we look at history as a vast series of stochastic events linked by relations of probabilistic causation? And does this permit us to make historical predictions after all?

Let's explore that idea. Imagine that history is entirely the product of a set of stochastic events connected with each other by fixed objective probabilities. And suppose we are interested in a particular kind of historical outcome -- say the emergence of central states involving dictatorship and democracy. We might represent this situation as a multi-level process of social-political complexification -- a kind of primordial soup of political development by opportunistic agents within a connected population in a spatial region. Suppose we postulate a simple political theory of competition and cooperation driving patterns of alliance formation, institution formation, and the aggregation of power by emerging institutions. (This sounds somewhat similar to Tilly's theory of state formation in Coercion, Capital and European States, A.D. 990 - 1992 and to Michael Mann's treatment of civilizations in The Sources of Social Power: Volume 1, A History of Power from the Beginning to AD 1760.)

Finally we need to introduce some kind of mechanism of invention -- of technologies, institutions, and values systems. This is roughly analogous to the mechanism of genetic mutation in the evolution of life.

Now we are ready to ask some large historical questions about state formation in numerous settings. What is the likelihood of the emergence of a stable system of self-governing communities? What is the likelihood that a given population will arrive at a group of inventions involving technology, institutions, and values systems that permit the emergence of central state capable of imposing its will over distance, collecting revenues to support its activities, and conducting warfare? And what is the likelihood of local failure, resulting in the extinction of the local population? We might look at the historical emergence of various political-economic forms such as plunder societies (Genghis Khan), varieties of feudalism, and medieval city states as different outcomes resulting from the throw of the dice in these different settings.

Self-governance seems like a fairly unlikely outcome within this set of assumptions. Empire and dictatorship seem like the more probable outcomes of the interplay of self-interest, power, and institutions. In order to get self-governance out of processes like these we need to identify a mechanism through which collective action by subordinate agents is possible. Such mechanisms are indeed familiar -- the pressures by subordinate but powerful actors in England leading to the reform of absolutist monarchy, the overthrow of the French monarchy by revolutionary uprisings, the challenges to the Chinese emperor represented by a series of major rebellions in the nineteenth century. But such counter-hegemonic processes are often failures, and even when successful they are often coopted by powerful insiders. These possibilities lead us to estimate a low likelihood of stable self-governance.

So this line of thought suggests that a stochastic model of the emergence of central states is possible but discouraging. Assign probabilities to the various kinds of events that need to occur at each of the several stages of civilizational development; run the model a large number of times; and you have a Monte Carlo model of the emergence of dictatorship and democracy. And the discouraging likelihood is that democratic self-governance is a rare outcome.

However, there are several crucial flaws in this analysis. First, the picture is flawed by the fact that history is made by purposive agents, not algorithms or mechanical devices. These actors are not characterized by fixed objective probabilities. Historical actors have preferences and take actions to influence outcomes at crucial points. Second, agents are not fixed over time, but rather develop through learning. They are complex adaptive agents. They achieve innovations in their practices just as the engineers and bureaucrats do. They develop and refine repertoires of resistance (Tilly). So each play of the game of political history is novel in important respects. History is itself influenced by previous history.

Finally, there is the familiar shortcoming of simulations everywhere: a model along these lines unavoidably requires making simplifying assumptions about the causal factors in play. And these simplifications can be shown to have important consequences for the sensitivity of the model.

So it is important to understand that social causation is generally probabilistic; but this fact does not permit us to assign objective probabilities to the emergence of central states, dictatorships, or democracies.

(See earlier posts on more successful efforts to use Bayesian methods to assess the likelihood of the emergence of specific outcomes in constrained historical settings;
link, link.)

The culture of an organization

It is often held that the behavior of a particular organization is affected by its culture. Two banks may have very similar organizational structures but show rather different patterns of behavior, and those differences are ascribed to differences in culture. What does this mean? Clifford Geertz is one of the most articulate theorists of culture -- especially in his earlier works. Here is a statement couched in terms of religion as a cultural system from The Interpretation Of Cultures. A religion is ...

(1) a system of symbols which act to (2) establish powerful, pervasive, and long-lasting moods and motivations in men by (3) formulating conceptions of a general order of existence and (4) clothing these conceptions with such an aura of factuality that (5) the moods and motivations seem uniquely realistic. (90)

And again:

The concept of culture I espouse, and whose utility the essays below attempt to demonstrate, is essentially a semiotic one. Believing, with Max Weber, that man is an animal suspended in webs of significance he himself has spun, I take culture to be those webs, and the analysis of it to be therefore not an experimental science in search of law but an interpretive one in search of meaning. (5)

On its face this idea seems fairly simple. We might stipulate that "culture" refers to a set of beliefs, values, and practices that are shared by a number of individuals within the group, including leaders, managers, and staff members. But, as we have seen repeatedly in other posts, we need to think of these statements in terms of a distribution across a population rather than as a uniform set of values.

Consider this hypothetical comparison of two organizations with respect to employees' attitudes towards working with colleagues of a different religion. (This example is fictitious.) Suppose that the employees of two organizations have been surveyed on the topic of their comfort level at working with other people of different religious beliefs, on a scale of 0-21. Low values indicate a lower level of comfort.

The blue organization shows a distribution of individuals who are on average more accepting of religious diversity than the gold organization. The weighted score for the blue population is about 10.4, in comparison to a weighted score of 9.9 for the gold population. This is a relatively small difference between the two populations; but it may be enough to generate meaningful differences in behavior and performance. If, for example, the attitude measured here leads to an increased likelihood for individuals to make disparaging comments about the co-worker's religion, then we might predict that the gold group will have a somewhat higher level of incidents of religious intolerance. And if we further hypothesize that a disparaging work environment has some effect on work productivity, then we might predict that the blue group will have somewhat higher productivity.

Current discussions of sexual harassment in the workplace are often couched in terms of organizational culture. It appears that sexual harassment is more frequent and flagrant in some organizations than others. Women are particularly likely to be harassed in a work culture in which men believe and act as though they are at liberty to impose sexual language and action on female co-workers and in which the formal processes of reporting of harassment are weak or disregarded. The first is a cultural fact and the second is a structural or institutional fact.

We can ask several causal questions about this interpretation of organizational culture. What are the factors that lead to the establishment and currency of a given profile of beliefs, values, and practices within an organization? And what factors exist that either reproduce those beliefs or undermine them? Finally we can ask what the consequences of a given culture profile are in the internal and external performance of the organization.

There seem to be two large causal mechanisms responsible for establishment and maintenance of a particular cultural constellation within an organization. First is recruitment. One organization may make a specific effort to screen candidates so as to select in favor of a particular set of values and attitudes -- acceptance, collaboration, trustworthiness, openness to others. And another may favor attitudes and values that are thought to be more directly related to profitability or employee malleability. These selection mechanisms can lead to significant differences in the overall culture of the organization. And the decision to orient recruitment in one way rather than another is itself an expression of values.

The second large mechanism is the internal socialization and leadership processes of the organization. We can hypothesize that an organization whose leaders and supervisors both articulate the values of equality and respect in the workplace and who demonstrate that commitment in their own actions will be one in which more people in the organization will adopt those values. And we can likewise hypothesize that the training and evaluation processes of an organization can be effective in cultivating the values of the organization. In other words, it seems evident that leadership and training are particularly relevant to the establishment of a particular organizational culture.

The other large causal question is how and to what extent cultural differences across organizations have effects on the performance and behavior of those organizations. We can hypothesize that differences in organizational values and culture lead to differences in behavior within the organization -- more or less collaboration, more or less harassment, more or less bad behavior of various kinds. These differences are themselves highly important. But we can also hypothesize that differences like these can lead to differences in organizational effectiveness. This is the central idea of the field of positive organizational studies. Scholars like Kim Cameron and others argue, on the basis of empirical studies across organizational settings, that organizations that embody the values of mutual acceptance, equality, and a positive orientation towards each others' contributions are in fact more productive organizations as well (Competing Values Leadership: Second Edition; link).

Is public opinion part of a complex system?

The worrisome likelihood that Russians and other malevolent actors are tinkering with public opinion in Western Europe and the United States through social media creates various kinds of anxiety. Are our democratic values so fragile that a few thousand Facebook or Twitter memes could put us on a different plane about important questions like anti-Muslim bigotry, racism, intolerance, or fanaticism about guns? Can a butterfly in Minsk create a thunderstorm of racism in Cincinnati? Have white supremacy and British ultra-nationalism gone viral?

There is an interesting analogy here with the weather. The weather next Wednesday is the net consequence of a number of processes and variables, none of which are enormously difficult to analyze. But in their complex interactions they create outcomes that are all but impossible to forecast over a period of more than three days. And this suggests the interesting idea that perhaps public opinion is itself the result of complex and chaotic processes that give rise to striking forms of non-linear change over time.

Can we do a better job of understanding the dynamics of public opinion by making use of the tools of complexity theory? Here is a summary description of complex systems provided by John Holland in Complexity: A Very Short Introduction:

Complexity, once an ordinary noun describing objects with many interconnected parts, now designates a scientific field with many branches. A tropical rainforest provides a prime example of a complex system. The rainforest contains an almost endless variety of species—one can walk a hundred paces without seeing the same species of tree twice, and a single tree may host over a thousand distinct species of insects. The interactions between these species range from extreme generalists (‘ army’ ants will consume most anything living in their path) to extreme specialists (Darwin’s ‘comet orchid’, with a foot-long nectar tube, can only be pollinated by a particular moth with a foot-long proboscis—neither would survive without the other). Adaptation in rainforests is an ongoing, relatively rapid process, continually yielding new interactions and new species (orchids, closely studied by Darwin, are the world’s most rapidly evolving plant form). This lush, persistent variety is almost paradoxical because tropical rainforests develop on the poorest of soils—the rains quickly leach all nutrients into the nearest creek. What makes such variety possible? (1)

Let's consider briefly how public opinion might fit into the framework of complexity theory. On the positive side, public opinion has some of the dynamic characteristics of systems that are often treated as being complex: non-linearity, inflection points, critical mass. Like a disease, a feature of public opinion can suddenly "go viral" -- reproduce many times more rapidly than in previous periods. And the collective phenomenon of public opinion has a feature of "self-causation" that finds parallels in other kinds of systems -- a sudden increase in the currency of a certain attitude or belief can itself accelerate the proliferation of the belief more broadly.

On the negative side, the causal inputs to public opinion dynamics do not appear to be particularly "complex" -- word-of-mouth, traditional media, local influencers, and the new factor of social media networks like Twitter, Weibo, or Facebook. We might conceptualize a given individual's opinion formation as the net result of information and influence received through these different kinds of inputs, along with some kind of internal cognitive processing. And the population's "opinions" are no more than the sum of the opinions of the various individuals.

Most fundamentally -- what are the "system" characteristics that are relevant to the dynamics of public opinion in a modern society? How does public opinion derive from a system of individuals and communication pathways?

This isn't a particularly esoteric question. We can define public opinion at the statistical aggregate of the distribution of beliefs and attitudes throughout a population -- recognizing that there is a distribution of opinion around every topic. For example, at present public opinion in the United States on the topic of President Trump is fairly negative, with a record low 35% approval rating. And the Pew Research Center finds that US public opinion sees racism as an increasingly important problem (link):



Complexity theorists like Scott Page and John Holland focus much attention on a particular subset of complex systems, complex adaptive systems (CAS). These are systems in which the agents are themselves subject to change. And significantly, public opinion in a population of human agents is precisely such a system. The agents change their opinions and attitudes as a result of interaction with other agents through the kinds of mechanisms mentioned here. If we were to model public opinion as a "pandemonium" process, then the possibility of abrupt non-linearities in a population becomes apparent. Assume a belief-transmission process in which individuals transmit beliefs to others with a volume proportional to their own adherence to the belief and the volume and number of other agents from whom they have heard the belief, and individuals adopt a belief in proportion to the number and volume of voices they hear that are espousing the belief. Contagion is no longer a linear relationship (exposure to an infected individual results in X probability of infection), but rather a non-linear process in which the previous cycle's increase leads to amplified infection rate in the next round.

Here is a good review article of the idea of a complex system and complexity science by Ladyman, Lambert and Wiesner (link, link). Here is a careful study of the diffusion of "fake news" by bots on Twitter (link, link). (The graphic at the top is taken from this article.) And here is a Ph.D. dissertation on modeling public opinion by Emily Cody (link).

Varieties of organizational dysfunction

Several earlier posts have made the point that important technology failures often include organizational faults in their causal background.

It is certainly true that most important accidents have multiple causes, and it is crucial to have as good an understanding as possible of the range of causal pathways that have led to air crashes, chemical plant explosions, or drug contamination incidents. But in the background we almost always find organizations and practices through which complex technical activities are designed, implemented, and regulated. Human actors, organized into patterns of cooperation, collaboration, competition, and command, are as crucial to technical processes as are power lines, cooling towers, and control systems in computers. So it is imperative that we follow the lead of researchers like Charles Perrow (The Next Catastrophe: Reducing Our Vulnerabilities to Natural, Industrial, and Terrorist Disasters), Kathleen Tierney (The Social Roots of Risk: Producing Disasters, Promoting Resilience), or Diane Vaughan (The Challenger Launch Decision: Risky Technology, Culture, and Deviance at NASA) and give close attention to the social- and organization-level failures that sometimes lead to massive technological failures.

It is useful to have a few examples in mind as we undertake to probe this question more deeply. Here are a number of important accidents and failures that have been carefully studied.

• Three Mile Island, Chernobyl nuclear disasters
• Challenger and Columbia space shuttle disasters
• Failure of United States anti-submarine warfare in 1942-43
• Flawed policy and decision-making in US leading to escalation of Vietnam War
• Flawed policy and decision-making in France leading to Dien Bien Phu defeat
• Failure of Nuclear Regulatory Commission to ensure reactor safety
• DC-10 design process
• Osprey design process
• failure of Federal flood insurance to appropriately guide rational land use
• FEMA failure in Katrina aftermath
• Design and manufacture of the Edsel sedan
• High rates of hospital-born infections in some hospitals

Examples like these allow us to begin to create an inventory of organizational flaws that sometimes lead to failures and accidents:

• siloed decision-making (design division, marketing division, manufacturing division all have different priorities and interests)
• lax implementation of formal processes
• strategic bureaucratic manipulation of outcomes 
• information withholding, lying
• corrupt practices, conflicts of interest and commitment
• short-term calculation of costs and benefits
• indifference to public goods
• poor evaluation of data; misinterpretation of data
• lack of high-level officials responsible for compliance and safety

These deficiencies may be analyzed in terms of a more abstract list of organizational failures:

• Poor decisions given existing priorities and facts
• poor priority-setting processes
• poor information-gathering and analysis
• failure to learn and adapt from changing circumstances
• internal capture of decision-making; corruption, conflict of interest
• vulnerability of decision-making to external pressures (external capture)
• faulty or ineffective implementation of policies, procedures, and regulations

******

Nancy Leveson is a leading authority on the systems-level causes of accidents and failures. A recent white paper can be found here. Here is the abstract for that paper:

New technology is making fundamental changes in the etiology of accidents and is creating a need for changes in the explanatory mechanisms used. We need better and less subjective understanding of why accidents occur and how to prevent future ones. The most effective models will go beyond assigning blame and instead help engineers to learn as much as possible about all the factors involved, including those related to social and organizational structures. This paper presents a new accident model founded on basic systems theory concepts. The use of such a model provides a theoretical foundation for the introduction of unique new types of accident analysis, hazard analysis, accident prevention strategies including new approaches to designing for safety, risk assessment techniques, and approaches to designing performance monitoring and safety metrics. (1; italics added)

Here is what Leveson has to say about the social and organizational causes of accidents:

2.1 Social and Organizational Factors

Event-based models are poor at representing systemic accident factors such as structural deficiencies in the organization, management deficiencies, and flaws in the safety culture of the company or industry. An accident model should encourage a broad view of accident mechanisms that expands the investigation from beyond the proximate events.

Ralph Miles Jr., in describing the basic concepts of systems theory, noted that:

Underlying every technology is at least one basic science, although the technology may be well developed long before the science emerges. Overlying every technical or civil system is a social system that provides purpose, goals, and decision criteria (Miles, 1973, p. 1).

Effectively preventing accidents in complex systems requires using accident models that include that social system as well as the technology and its underlying science. Without understanding the purpose, goals, and decision criteria used to construct and operate systems, it is not possible to completely understand and most effectively prevent accidents. (6)

Organizational dysfunction

What is a dysfunction when it comes to the normal workings of an organization? In order to identify dysfunctions we need to have a prior conception of the "purpose" or "agreed upon goals" of an organization. Fiscal agencies collect taxes; child protection services work to ensure that foster children are placed in safe and nurturing environments; air travel safety regulators ensure that aircraft and air fields meet high standards of maintenance and operations; drug manufacturers produce safe, high-quality medications at a reasonable cost. A dysfunction might be defined as an outcome for an organization or institution that runs significantly contrary to the purpose of the organization. We can think of major failures in each of these examples.

But we need to make a distinction between failure and dysfunction. The latter concept is systemic, having to do with the design and culture of the organization. Failure can happen as a result of dysfunctional arrangements; but it can happen as a result of other kinds of factors as well. For example, the Tylenol crisis of 1982 resulted from malicious tampering by an external third party, not organizational dysfunction.

Here is an example from a Harvard Business Review article by Gill Corkindale indicating some of the kinds of dysfunction that can be identified in contemporary business organizations:

Poor organizational design and structure results in a bewildering morass of contradictions: confusion within roles, a lack of co-ordination among functions, failure to share ideas, and slow decision-making bring managers unnecessary complexity, stress, and conflict. Often those at the top of an organization are oblivious to these problems or, worse, pass them off as or challenges to overcome or opportunities to develop. (link)

And the result of failures like these is often poor performance and sometimes serious crisis for the organization or its stakeholders.

But -- as in software development -- it is sometimes difficult to distinguish between a feature and a bug. What is dysfunctional for the public may indeed be beneficial for other actors who are in a position to influence the design and workings of the organization. This is the key finding of researchers like Jack Knight, who argues in Institutions and Social Conflict for the prevalence of conflicting interests in the design and operations of many institutions and organizations; link. And it follows immediately from the approach to organizations encapsulated in the Fligstein and McAdam theory of strategic action fields (link).

There is an important related question to consider: why do recognized dysfunctional characteristics persist? When a piano is out of tune, the pianist and the audience insist on a professional tuning. When the Nuclear Regulatory Commission persistently fails to enforce its regulations through rigorous inspection protocols, nothing happens (Union of Concerned Scientists, link; Perrow, link). Is it that the individuals responsible for the day-to-day functioning of the organization are complacent or unmotivated? Is it that there are contrary pressures that arise to oppose corrective action? Or, sometimes, is it that the adjustments needed to correct one set of dysfunctions can be expected to create another, even more harmful, set of bad outcomes?

One intriguing hypothesis is that correction of dysfunctions requires observation, diagnosis, and incentive alignment. It is necessary that some influential actor or group should be able to observe the failure; it should be possible to trace the connection between the failure and the organizational features that lead to it; and there should be some way of aligning the incentives of the powerful actors within and around the organization so that their best interests are served by their taking the steps necessary to correct the dysfunction. If any of these steps is blocked, then a dysfunctional organization can persist indefinitely.

The failures of Soviet agriculture were observable and the links between organization and farm inefficiency were palpable; but the Soviet public had not real leverage with respect to the ministries and officials who ran the agricultural system. Therefore Soviet officials had no urgent incentive to reform agriculture. So the dysfunctions of collective farming were not corrected until the collapse of the USSR. A dysfunction in a corporation within a market economy that significantly impacts its revenues and profits will be noticed by shareholders, and pressure will be exerted to correct the dysfunction. The public has a strong interest in nuclear reactor safety; but its interests are weak and diffused when compared to the interests of the industry and its lobbyists; so Congressional opposition to reform of the agency remains strong. The same could be said with respect to the current crisis at the Consumer Financial Protection Bureau; the influence of the financial industry and its lobbyists can be concentrated in a way that the interests of the public cannot.

Charles Perrow has written extensively on the failures of the US regulatory sector (link). Here is his description of regulatory capture in the nuclear power industry:

Nuclear safety is problematic when nuclear plants are in private hands because private firms have the incentive and, often, the political and economic power to resist effective regulation. That resistance often results in regulators being captured in some way by the industry. In Japan and India, for example, the regulatory function concerned with safety is subservient to the ministry concerned with promoting nuclear power and, therefore, is not independent. The United States had a similar problem that was partially corrected in 1975 by putting nuclear safety into the hands of an independent agency, the Nuclear Regulatory Commission (NRC), and leaving the promotion of nuclear power in the hands of the Energy Department. Japan is now considering such a separation. It should make one. Since the accident at Fukushima, many observers have charged that there is a revolving door between industry and the nuclear regulatory agency in Japan -- what the New York Times called a "nuclear power village" -- compromising the regulatory function. (link)

New perspectives on Chinese authoritarianism

The question of China's political future is an important one and a difficult one. Will China evolve towards a political system that embodies real legal protections for the rights of its citizens and some version of democratic institutions of government? Or will it remain an authoritarian single-party state in which government and the party decide the limits of freedom and the course of economic and social policy?

Two recent books are worth reading in this context, and they seem to point to rather different answers. Ya-Wen Lei's The Contentious Public Sphere: Law, Media, and Authoritarian Rule in China makes the case for a broadening sphere of public discourse and debate in China, which seems to suggest the possibility of a gradual loosening of governmental control of thought and action. Wenfang Tang's Populist Authoritarianism: Chinese Political Culture and Regime Sustainability on the other hand makes the case for a distinctive version of populist authoritarianism in China that may have the resources it needs to retain power for a very long time. Neither scholar is dogmatic about his or her findings, but they give rather different pictures of the evolution of China's polity in the next several decades.

The two books use rather different kinds of data. Tang relies primarily on various surveys of Chinese public opinion, whereas Lei's research relies on a range of qualitative and observational data about the contents of China's legal system, media, and social media. She makes use of newspaper archives, legal texts, interviews, online texts from Internet forums, and survey data (lc 466).

Tang's book begins with several paradoxical facts. One is that the Chinese state already embodies a kind of democratic responsiveness, which he refers to as "Mass Line" politics. According to this political ideology, the Party represents the interests of the masses, and it must be responsive to the interests and demands of workers and peasants. So the CCP is sometimes responsive to demands expressed through public demonstrations and protests. Here are a few of Tang's comments about the Mass Line ideology: "Some observers see the totalitarian nature of the Mass Line.... Other scholars, however, see the empowerment of society under the Mass Line.... Others describe the Mass Line as a democratic decision-making process" (kl 357-388). But Tang's own view appears to be that the Party's adherence to the ideology of the Mass Line makes for a compelling imperative towards paying attention to the attitudes and interests of ordinary peasants and workers, and towards improving their material conditions of life.

The other paradoxical fact in Tang's account is that China's government commands support from a remarkably high percentage of its citizens. Using survey research, Tang reports that there are issues of concern to the Chinese public (corruption, environment, land use policy), but that the large majority of Chinese people support the single-party government of the CCP.

The 2005–2008 5th wave of the WVS [World Values Survey] coordinated by the University of Michigan further indicated that Chinese respondents expressed the strongest support for political institutions including the military, the police, the legal system, the central government, the Communist Party, the national legislature, and the civil service. (kl 712)

But Tang also notes that surveys indicate a low level of "happiness" and satisfaction by Chinese citizens. In the WVS 2005-2008 survey "China ranked at the very bottom of this happiness index (65). Above China were eastern Germany (65.5), Slovenia and South Korea (66), India (67), Taiwan and Spain (68), Italy and Chile (69)," along with many other countries. This presents a third paradox in Chinese political realities; low citizen satisfaction is often associated with low approval of government, but this is not the case in China at present. Tang observes, "there seems to be a contradiction between the low level of happiness and the high level of regime support" (kl 774).

Here is how Tang characterizes China's particular version of "populist authoritarianism". China's particular version involves ...

the Mass Line ideology, strong interpersonal trust and rich social capital, individual political activism and political contention, weak political institutions and an underdeveloped civic society, an often paranoid and highly responsive government, and strong regime support. (kl 240)

What strategies and mechanisms permit an authoritarian state to maintain its stability over time, beyond the exercise of force? Tang supports the "political culture" strand of thinking about politics; he believes that the beliefs, identities, and attitudes that citizens have are crucial for the way in which politics unfolds in the country. One factor that Tang rates as particularly favorable for regime stability in China is the high degree of nationalism that Chinese people share, according to survey data. Survey data support the finding that Chinese people have a high level of identification with the value and importance of China as a nation. And, significantly, the central government makes explicit efforts to reinforce popular nationalist sentiment.

While Chinese civilization is an ancient concept, Chinese nationalism is a relatively new idea in contemporary China. It is constructed by the CCP to incorporate a multi-ethnic state that was inherited from the Qing dynasty. It has been used by the CCP to justify its resistance to liberal democracy which is often associated with Western imperialist invasion of China in the 19th and early 20th centuries. More importantly, nationalism is an inseparable component of contemporary Chinese political culture that provides the soil for the CCP to nurture its legitimacy. (kl 1364)

So Tang's conclusion about regime stability in China is tentative, but he leaves open the possibility that the CCP and single-party government has enough resources available to it to survive as a popular and populist government in China for an extended period of time. He suggests that populist authoritarianism is potentially a stable system of government -- anti-democratic in the traditional western sense, but responsive enough to the demands and interests of ordinary citizens to permit it to maintain high levels of legitimacy and acceptance by the broad public over an extended period of time.

Now let's look at the political dynamics described in Ya-Wen Lei's very interesting 2018 book, The Contentious Public Sphere: Law, Media, and Authoritarian Rule in China. Lei too regards China as an authoritarian state. And yet Chinese society possesses a surprising degree of public contestation over important social issues.

Authoritarian states, by definition, undermine civil society—the basis on which the public sphere is built—thus conventional wisdom tells us that the conditions for political life and a public sphere in such contexts are likely to be quite bleak and suffocating (Habermas 1996, 369). Yet, when I looked at what was going on in China, I saw lively political discussion, contention, and engagement—in short, the emergence of a vibrant public sphere, against all apparent odds. (kl 264)

In describing this "unruly sphere capable of generating issues and agendas not set by the Chinese state" (kl 278) Lei is primarily referring to the cell-phone supported social media world in China, within which Weibo is the primary platform. And Lei takes the position that the emergence of this public sphere in the early 2000s was an unintended consequence of "authoritarian modernization".

I argue that the rise of China’s contentious public sphere was an unintended consequence of the Chinese state’s campaign of authoritarian modernization. The government desperately needed to modernize in the aftermath of the Cultural Revolution. To do so, the state institutionalized the double-edged instruments of modern law, marketized media, and the Internet. It sought to utilize but also contain these instruments, recognizing the potential risk each posed of empowering professionals and citizens and destabilizing political control. Nonetheless, the state’s choices set in motion complex and interconnected processes beyond its control. Building legal and media institutions and adopting information technologies, paired with political fragmentation and marketization, increased the capabilities of citizens and professionals, encouraged the formation of multiple overlapping social networks of collaboration, engendered widespread legal and rights consciousness, and created a space for contentious politics. Through everyday practices and the production of so-called public opinion incidents (yulun shijian), media and legal professionals, public opinion leaders, activists, NGOs, and netizens translated individual grievances into collective contention—and in so doing, facilitated the rise of a contentious public sphere. (kl 290)

Lei maintains that the state was aware of this risk and has taken measures to ameliorate it; but she also believes that the forces leading to open debate and social networks that are relatively free to engage in these kinds of discussions are more numerous than authoritarian censorship can manage to control. President Xi's current crackdown on ideological deviation is the most recent version of the state's effort at control; but the logic of Lei's argument suggests that these repressive measures will not succeed in eliminating the emerging public sphere. She refers to this situation as the "authoritarian dilemma of modernization":

Yet the Chinese state’s authoritarian modernization project has encountered what I call an “authoritarian dilemma of modernization.” On the one hand, the state has to build economic, legal, and political institutions to pursue socioeconomic development. The state also needs capable professionals and citizens to make institutions work, produce economic growth, and ultimately achieve the goal of modernization. These capable agents need to be educated and have knowledge, information, and even some autonomy to participate in the tasks designated by the state. (lc 354)

New legal institutions and new forms of information technology create opportunities for increasingly well-educated people to find new ways of pursuing debates and advocating for policies that the state would prefer not to have to consider.

In contrast to Tang's "populist authoritarianism", Lei refers to a "fragmented and adaptive authoritarianism" in China. And she argues that this fragmentation (through new institutions, new legal frameworks, and new ways of communicating and disseminating divergent opinions) has led to the possibility of social changes emerging that were not intended or sanctioned by the governing elites.

In an interesting way Lei's view of fragmented authoritarianism has some themes in common with Fligstein and McAdam's ideas of organizations as "strategic action fields" (link); different actors within the Chinese polity are able to gain resources and leverage to pursue their own concerns. Lei's analysis emphasizes the shifting resources available to various actors within the field of politics, including new legal institutions and new opportunities for communications and interaction through the Internet. The strategic-action-field theory does not presuppose that "governors" or "insurgents" automatically have the upper hand; instead, it posits that change within a strategic action field is highly contingent, with a variety of possible outcomes. And this indeed seems like a very good description of Chinese politics.

(Here is an earlier post on Martin Whyte's research on public opinions about social justice in China in Myth of the Social Volcano: Perceptions of Inequality and Distributive Injustice in Contemporary China; link.)