Sexual harassment in academic contexts

Sexual harassment of women in academic settings is regrettably common and pervasive, and its consequences are grave. At the same time, it is a remarkably difficult problem to solve. The "me-too" movement has shed welcome light on specific individual offenders and has generated more awareness of some aspects of the problem of sexual harassment and misconduct. But we have not yet come to a public awareness of the changes needed to create a genuinely inclusive and non-harassing environment for women across the spectrum of mistreatment that has been documented. The most common institutional response following an incident is to create a program of training and reporting, with a public commitment to investigating complaints and enforcing university or institutional policies rigorously and transparently. These efforts are often well intentioned, but by themselves they are insufficient. They do not address the underlying institutional and cultural features that make sexual harassment so prevalent.

The problem of sexual harassment in institutional contexts is a difficult one because it derives from multiple features of the organization. The ambient culture of the organization is often an important facilitator of harassing behavior -- often enough a patriarchal culture that is deferential to the status of higher-powered individuals at the expense of lower-powered targets. There is the fact that executive leadership in many institutions continues to be predominantly male, who bring with them a set of gendered assumptions that they often fail to recognize. The hierarchical nature of the power relations of an academic institution is conducive to mistreatment of many kinds, including sexual harassment. Bosses to administrative assistants, research directors to post-docs, thesis advisors to PhD candidates -- these unequal relations of power create a conducive environment for sexual harassment in many varieties. In each case the superior actor has enormous power and influence over the career prospects and work lives of the women over whom they exercise power. And then there are the habits of behavior that individuals bring to the workplace and the learning environment -- sometimes habits of masculine entitlement, sometimes disdainful attitudes towards female scholars or scientists, sometimes an underlying willingness to bully others that finds expression in an academic environment. (A recent issue of the Journal of Social Issues (link) devotes substantial research to the topic of toxic leadership in the tech sector and the "masculinity contest culture" that this group of researchers finds to be a root cause of the toxicity this sector displays for women professionals. Research by Jennifer Berdahl, Peter Glick, Natalya Alonso, and more than a dozen other scholars provides in-depth analysis of this common feature of work environments.)

The scope and urgency of the problem of sexual harassment in academic contexts is documented in excellent and expert detail in a recent study report by the National Academies of Sciences, Engineering, and Medicine (link). This report deserves prominent discussion at every university.

The study documents the frequency of sexual harassment in academic and scientific research contexts, and the data are sobering. Here are the results of two indicative studies at Penn State University System and the University of Texas System:

The Penn State survey indicates that 43.4% of undergraduates, 58.9% of graduate students, and 72.8% of medical students have experienced gender harassment, while 5.1% of undergraduates, 6.0% of graduate students, and 5.7% of medical students report having experienced unwanted sexual attention and sexual coercion. These are staggering results, both in terms of the absolute number of students who were affected and the negative effects that these  experiences had on their ability to fulfill their educational potential. The University of Texas study shows a similar pattern, but also permits us to see meaningful differences across fields of study. Engineering and medicine provide significantly more harmful environments for female students than non-STEM and science disciplines. The authors make a particularly worrisome observation about medicine in this context:

The interviews conducted by RTI International revealed that unique settings such as medical residencies were described as breeding grounds for abusive behavior by superiors. Respondents expressed that this was largely because at this stage of the medical career, expectation of this behavior was widely accepted. The expectations of abusive, grueling conditions in training settings caused several respondents to view sexual harassment as a part of the continuum of what they were expected to endure. (63-64)

The report also does an excellent job of defining the scope of sexual harassment. Media discussion of sexual harassment and misconduct focuses primarily on egregious acts of sexual coercion. However, the  authors of the NAS study note that experts currently encompass sexual coercion, unwanted sexual attention, and gender harassment under this category of harmful interpersonal behavior. The largest sub-category is gender harassment:

"a broad range of verbal and nonverbal behaviors not aimed at sexual cooperation but that convey insulting, hostile, and degrading attitudes about" members of one gender (Fitzgerald, Gelfand, and Drasgow 1995, 430). (25)

The "iceberg" diagram (p. 32) captures the range of behaviors encompassed by the concept of sexual harassment. (See Leskinen, Cortina, and Kabat 2011 for extensive discussion of the varieties of sexual harassment and the harms associated with gender harassment.)

The report emphasizes organizational features as a root cause of a harassment-friendly environment.

By far, the greatest predictors of the occurrence of sexual harassment are organizational. Individual-level factors (e.g., sexist attitudes, beliefs that rationalize or justify harassment, etc.) that might make someone decide to harass a work colleague, student, or peer are surely important. However, a person that has proclivities for sexual harassment will have those behaviors greatly inhibited when exposed to role models who behave in a professional way as compared with role models who behave in a harassing way, or when in an environment that does not support harassing behaviors and/or has strong consequences for these behaviors. Thus, this section considers some of the organizational and environmental variables that increase the risk of sexual harassment perpetration. (46)

Some of the organizational factors that they refer to include the extreme gender imbalance that exists in many professional work environments, the perceived absence of organizational sanctions for harassing behavior, work environments where sexist views and sexually harassing behavior are modeled, and power differentials (47-49). The authors make the point that gender harassment is chiefly aimed at indicating disrespect towards the target rather than sexual exploitation. This has an important implication for institutional change. An institution that creates a strong core set of values emphasizing civility and respect is less conducive to gender harassment. They summarize this analysis in the statement of findings as well:

Organizational climate is, by far, the greatest predictor of the occurrence of sexual harassment, and ameliorating it can prevent people from sexually harassing others. A person more likely to engage in harassing behaviors is significantly less likely to do so in an environment that does not support harassing behaviors and/or has strong, clear, transparent consequences for these behaviors. (50)

So what can a university or research institution do to reduce and eliminate the likelihood of sexual harassment for women within the institution? Several remedies seem fairly obvious, though difficult.

• Establish a pervasive expectation of civility and respect in the workplace and the learning environment
• Diffuse the concentrations of power that give potential harassers the opportunity to harass women within their domains
• Ensure that the institution honors its values by refusing the "star culture" common in universities that makes high-prestige university members untouchable
• Be vigilant and transparent about the processes of investigation and adjudication through which complaints are considered
• Create effective processes that ensure that complainants do not suffer retaliation
• Consider candidates' receptivity to the values of a respectful, civil, and non-harassing environment during the hiring and appointment process (including research directors, department and program chairs, and other positions of authority)
• Address the gender imbalance that may exist in leadership circles

As the authors put the point in the final chapter of the report:

Preventing and effectively addressing sexual harassment of women in colleges and universities is a significant challenge, but we are optimistic that academic institutions can meet that challenge--if they demonstrate the will to do so. This is because the research shows what will work to prevent sexual harassment and why it will work. A systemwide change to the culture and climate in our nation's colleges and universities can stop the pattern of harassing behavior from impacting the next generation of women entering science, engineering, and medicine. (169)

System effects

Quite a few posts here have focused on the question of emergence in social ontology, the idea that there are causal processes and powers at work at the level of social entities that do not correspond to similar properties at the individual level. Here I want to raise a related question, the notion that an important aspect of the workings of the social world derives from "system effects" of the organizations and institutions through which social life transpires. A system accident or effect is one that derives importantly from the organization and configuration of the system itself, rather than the specific properties of the units.

What are some examples of system effects? Consider these phenomena:

• Flash crashes in stock markets as a result of automated trading
• Under-reporting of land values in agrarian fiscal regimes 
• Grade inflation in elite universities 
• Increase in product defect frequency following a reduction in inspections 
• Rising frequency of industrial errors at the end of work shifts 

Here is how Nancy Leveson describes systems causation in Engineering a Safer World: Systems Thinking Applied to Safety:

Safety approaches based on systems theory consider accidents as arising from the interactions among system components and usually do not specify single causal variables or factors. Whereas industrial (occupational) safety models and event chain models focus on unsafe acts or conditions, classic system safety models instead look at what went wrong with the system's operation or organization to allow the accident to take place. (KL 977)

Charles Perrow offers a taxonomy of systems as a hierarchy of composition in Normal Accidents: Living with High-Risk Technologies:

Consider a nuclear plant as the system. A part will be the first level -- say a valve. This is the smallest component of the system that is likely to be identified in analyzing an accident. A functionally related collection of parts, as, for example, those that make up the steam generator, will be called a unit, the second level. An array of units, such as the steam generator and the water return system that includes the condensate polishers and associated motors, pumps, and piping, will make up a subsystem, in this case the secondary cooling system. This is the third level. A nuclear plan has around two dozen subsystems under this rough scheme. They all come together in the fourth level, the nuclear plant or system. Beyond this is the environment. (65)

Large socioeconomic systems like capitalism and collectivized socialism have system effects -- chronic patterns of low productivity and corruption in the latter case, a tendency to inequality and immiseration in the former case. In each case the observed effect is the result of embedded features of property and labor in the two systems that result in specific kinds of outcomes. And an important dimension of social analysis is to uncover the ways in which ordinary actors pursuing ordinary goals within the context of the two systems, lead to quite different outcomes at the level of the "mode of production". And these effects do not depend on there being a distinctive kind of actor in each system; in fact, one could interchange the actors and still find the same macro-level outcomes.

Here is a preliminary effort at a definition for this concept in application to social organizations:

A system effect is an outcome that derives from the embedded characteristics of incentive and opportunity within a social arrangement that lead normal actors to engage in activity leading to the hypothesized aggregate effect.

Once we see what the incentive and opportunity structures are, we can readily see why some fraction of actors modify their behavior in ways that lead to the outcome. In this respect the system is the salient causal factor rather than the specific properties of the actors -- change the system properties and you will change the social outcome.

When we refer to system effects we often have unintended consequences in mind -- unintended both by the individual actors and the architects of the organization or practice. But this is not essential; we can also think of examples of organizational arrangements that were deliberately chosen or designed to bring about the given outcome. In particular, a given system effect may be intended by the designer and unintended by the individual actors. But when the outcomes in question are clearly dysfunctional or "catastrophic", it is natural to assume that they are unintended. (This, however, is one of the specific areas of insight that comes out of the new institutionalism: the dysfunctional outcome may be favorable for some sets of actors even as they are unfavorable for the workings of the system as a whole.)

 
Another common assumption about system effects is that they are remarkably stable through changes of actors and efforts to reverse the given outcome. In this sense they are thought to be somewhat beyond the control of the individuals who make up the system. The only promising way of undoing the effect is to change the incentives and opportunities that bring it about. But to the extent that a given configuration has emerged along with supporting mechanisms protecting it from deformation, changing the configuration may be frustratingly difficult.

Safety and its converse are often described as system effects. By this is often meant two things. First, there is the important insight that traditional accident analysis favors "unit failure" at the expense of more systemic factors. And second, there is the idea that accidents and failures often result from "tightly linked" features of systems, both social and technical, in which variation in one component of a system can have unexpected consequences for the operation of other components of the system. Charles Perrow describes the topic of loose and tight coupling in social systems in Normal Accidents; 89 ff,)

Social mobility disaggregated

There is a new exciting and valuable contribution from the research group around Raj Chetty, Nathan Hendren, and John Friedman, this time on the topic of neighborhood-level social mobility. (Earlier work highlighted measures of the impact on social mobility contributed by university education across the country. This work is presented on the Opportunity Insights website; link, link. Here is an earlier post on that work; link.) In the recently released work Chetty and his colleagues have used census data to compare incomes of parents and children across the country by neighborhood of birth, with the ability to disaggregate by race and gender, and the results are genuinely staggering. Here is a report on the project on the US Census website; link. The interactive dataset and mapping app are provided here (link). The study identifies neighborhoods of origin; characteristics of parents and neighborhoods; and characteristics of children.

Here are screenshots of metropolitan Detroit representing the individual incomes of the children (as adults) based on their neighborhoods of origin for all children, black children, and white children. (Of course a percentage of these individuals no longer live in the original neighborhood.) There are 24 outcome variables included as well as 13 neighborhood characteristics, and it is possible to create maps based on multiple combinations of these variables. It is also possible to download the data.

Children born in Highland Park, Michigan earned an average individual income as adults in 2014-15 of $18K; children born in Plymouth, Michigan earned an average individual income as adults of $42K. It is evident that these differences in economic outcomes are highly racialized; in many of the tracts in the Detroit area there are "insufficient data" for either black or white individuals to provide average data for these sub-populations in the given areas. This reflects the substantial degree of racial segregation that exists in the Detroit metropolitan area. (The project provides a special study of opportunity in Detroit, "Finding Opportunity in Detroit".)

This dataset is genuinely eye-opening for anyone interested in the workings of economic opportunity in the United States. It is also valuable for public policy makers at the local and higher levels who have an interest in improving outcomes for children in poverty. It is possible to use the many parameters included in the data to probe for obstacles to socioeconomic progress that might be addressed through targeted programs of opportunity enhancement.

(Here is a Brookings description of the social mobility project's central discoveries; link.)

Emotions as neurophysiological constructs

Are emotions real? Are they hardwired to our physiology? Are they pre-cognitive and purely affective? Was Darwin right in speculating that facial expressions are human universals that accurately represent a small repertoire of emotional experiences (The Expression of the Emotions in Man and Animals)? Or instead are emotions a part of the cognitive output of the brain, influenced by context, experience, expectation, and mental framework? Lisa Feldman Barrett is an accomplished neuroscientist who addresses all of these questions in her recent book How Emotions Are Made: The Secret Life of the Brain, based on several decades of research on the emotions. The book is highly interesting, and has important implications for the social sciences more broadly.

Barrett's core view is that the received theory of the emotions -- that they are hardwired and correspond to specific if unknown neurological groups, connected to specific physiological and motor responses -- is fundamentally wrong. She marshals a great deal of experimental evidence to the incorrectness of that theory. In its place she argues that emotional responses and experiences are the result of mental, conceptual, and cognitive construction by our central nervous system, entirely analogous to our ability to find meaning in a visual field of light and dark areas in order to resolve it as a bee (her example). The emotions are like perception more generally -- they result from an active process in which the brain attempts to impose order and pattern on sensory stimulation, a process she refers to as "simulation". She refers to this as the theory of constructed emotion (30). In brief:

Emotions are not reactions to the world. You are not a passive receiver of sensory input but an active constructor of your emotions. From sensory input and past experience, your brain constructs meaning and prescribes action. If you didn't have concepts that represent your past experience, all your sensory inputs would just be noise. (31)

And further:

Particular concepts like "Anger" and "Distrust" are not genetically determined. Your familiar emotion concepts are built-in only because you grew up in a particular social context where those emotion concepts are meaningful and useful, and your brain applies them outside your awareness to construct your experiences. (33)

This theory has much in common with theorizing about the nature of perception and thought within cognitive psychology, where the constructive nature of perception and representation has been a core tenet. Paul Kolers' motion perception experiments in the 1960s and 1970s established that perception is an active and constructive process, not a simple rendering of information from the retina into visual diagrams in the mind (Aspects of Motion Perception). And Daniel Dennett's Consciousness Explained argues for a "multiple drafts" theory of conscious experience which once again emphasizes the active and constructive nature of consciousness.

One implication of Barrett's theory is that emotions are concept-dependent. We need to learn the terms for emotions in our ambient language community before we can experience them. The emotions we experience are conceptually loaded and structured.

People who exhibit low emotional granularity will have only a few emotion concepts. In English, they might have words in their vocabulary like "sadness," "fear," "guilt," "shame," "embarrassment," "irritation," "anger," and "contempt," but those words all correspond to the same concept whose goal is something like "feeling unpleasant." This person has a few tools -- a hammer and Swiss Army knife. (106)

In a later chapter Barrett takes her theory in a Searle-like direction by emphasizing the inherent and irreducible constructedness of social facts and social relations (chapter 7). Without appropriate concepts we cannot understand or represent the behaviors and interactions of people around us; and their interactions depend inherently on the conceptual systems or frames within which we place their actions. Language, conceptual frames, and collective intentionality are crucial constituents of social facts, according to this perspective. I find Searle's arguments on this subject less than convincing (link), and I'm tempted to think that Barrett is going out on a limb by embracing his views more extensively than needed for her own theory of the emotions.

I find Barrett's work interesting for a number of reasons. One is the illustration it provides of human plasticity and heterogeneity. "Any category of emotion such as "Happiness" or "Guilt" is filled with variety" (35). Another is the methodological sophistication Barrett demonstrates in her refutation of two thousand years of received wisdom about the emotions, from Aristotle and Plato to Paul Ekman and colleagues. This sophistication extends to her effort to avoid language in describing emotions and research strategies that embeds the ontology of the old view -- an ontology that reifies particular emotions in the head and body of the other human being (40). She correctly observes that language like "detecting emotion X in the subject" implies that the psychological condition exists as a fixed reality in the subject; whereas the whole point of her theory is that the experience of disgust or happiness is a transient and complex construction by the brain behind the scenes of our conscious experience. She is "anti-realist" in her treatment of emotion. "We don't recognize emotions or identify emotions: we construct our own emotional experiences, and our perceptions of others' emotions, on the spot, as needed, through a complex interplay of systems" (40). And finally, her theory of emotion as a neurophysiological construct has a great deal of credibility -- its internal logic, its fit with current understandings of the central nervous system, its convergence with cognitive psychology and perception theory, and the range of experimental evidence that Barrett brings to bear.