9/13 Author's Roundtable 1: Kathleen Woodward, Statistical Panic
Responses from Ericka Beckman, Jane Desmond, Elizabeth Hoiem

Tuesday, September 14, 2010

posted under , , , , , by Unit for Criticism

[On Monday, September 13, the Unit for Criticism held the first of its Fall 2010 Author’s Roundtables. The Unit hosted Kathleen Woodward who discussed her latest book, Statistical Panic: Cultural Politics and the Poetics of Emotions (Duke 2009). The below contributions are from all three
respondents: Ericka Beckman, Jane Desmond, and Elizabeth Hoiem]

The 'New Sites' of Feeling: Response 1
Written by Ericka Beckman (Spanish/Comparative Literature)

In the second part of her book Statistical Panic, Kathleen Woodward draws from Raymond Williams’ notion of “structures of feeling” to explore some of the new feelings /intensities that cut across contemporary U.S. culture. An alternate definition she offers is that of “familiar feelings in new sites” (135), including, to wit, feeling for non-human cyborgs, bureaucratic rage, and statistical panic. In the case of bureaucratic rage (the evocative term is Woodward’s), the individual directs an emotional response towards the impersonal institution: the credit bureau, the insurance company. Statistical panic is a coinage used to refer to the uncertainty of the individual with the aggregate, an individual who when looking at the statistic (one in x number of women will develop breast cancer before the age of 45) is forced to manage her own risk.

And indeed the concept of risk becomes crucial to the generation and expression of bureaucratic rage and statistical panic. Drawing from work by Ian Hacking, and Zygmut Bauman, among others, Woodward identifies the concept of risk society as a social body in which private individuals are forced to constantly assess and manage risks to their physical health, financial future, emotional well-being, etc. For Woodward, statistics—the realm of probability—is an aspect of risk society that deserves attention as a site of proliferating affects, which, when studied can lead to better understandings of social experience and of institutions in our cultural moment.

In studying the emergence of new feelings, Woodward places special emphasis on narratives of illness. There are compelling reasons why Woodward focuses on illness narratives, memoirs in particular: first, because of the potency of the emotions generated by mortality: loss and grief; and, in a related vein, because late capitalism (or neoliberalism) has fomented unsustainable modes of caring for others. We live in a society health care not a right, but a commodity that the market should make available to those who can afford it. Second, Woodward argues that illness memoirs “serve the important cultural function of transcending the divisive identity politics of the past twenty-five years that have fragmented the body politic. For if there is one thing that is certain it is that the experience of illness crosses differences” (175). We are all held in the thrall of bureaucratic rage at insurance companies, at the FDA for not approving life-saving drugs, etc.

Yet I would stress, that precisely because we all inhabit a privatized and segmented risk society, some are more likely to die than others (those with no health insurance, for example, or those who suffer from conditions for which bracelets are not worn, or charity runs not organized). The structure of feeling may cross differences of age, class, race, gender but the experience within that structure of feeling is more likely to correspond with the visible segmentations inscribed within the social body of capitalism.

Statistical bewilderment: affects of financial crisis
Thinking with Woodward, the question I want to entertain for a moment is what happens if we turn our attention away from the medical establishment and disease, to turn to the financial sector, which, especially in the aftermath of the financial crisis of 2008, are likely to be generating new intensities and feelings. Among these we might identify: statistical bewilderment. If statistical panic refers to the uncertainty of individual faced with the solid certainty of the statistic (someone will die of Huntington’s, I just hope it’s not me), statistical bewilderment would mark the uncertainty of the individual before failure to predict what just months before the crisis had been unimaginable: the near collapse of the banking sector; the failure of risk managers to foresee the consequences of overextension; and, of course the failure to fathom the devastation wrought in the immediate aftermath of financial crisis: massive job loss, defaults on mortgages, evictions. These experiences will not be spread evenly among population, but will nonetheless provide ground for emergent affective dispositions and emotions.

An affect experienced in the midst of statistical bewilderment might be the “cool” disposition of “cynicism,” recently discussed by Slavoj Zizek as as a falsely post-ideological form of skepticism, by which I affirm my disagreement with what is going on, but accept it nonetheless under the assumption that it cannot be changed. The logic goes like this: “Wall Street bankers do not deserve such huge bonuses, but we must pay them so that they don’t wreck what is left of the financial edifice. It’s unfair, but that is just how it goes.” This feeling as non-feeling, I think, has a calming effect, in that it wills a return to “normalcy” by disavowing the uncertainty and instability that has just been revealed. (ideolgies have affects).

A second feeling generated by financial crisis is of course anger—directed at the banks, at CEOs, at politicians. On the surface, this seems like a more productive response to bewilderment. For only anger might lead us understand the nature of the calamity (in the Marxist terms if prefer
how tiny class of capitalists is able to ruin the whole credit system while enriching themselves). But the unsettling fact is that the most vociferously angry response to financial disaster and devastation has come from the populist right, one that sees a murkily conceived “state socialism”—and not the system of private accumulation—as causing the lamentable financial state we are in today.

The emotions of bad others; or, the emotions of others we don’t like
This brings me to a second point of engagement with Statistical Panic. If I understand Woodward’s project correctly, it is through engagement with the emotions that we can reach understandings of the self, but also of institutions: the risk society, the bureaucracy, etc. For the most part, Woodward reads novels and memoirs in which emotional responses are credited with having an “epistemological edge”: Virigina Woolf’s anger in A Room of One’s Own allows her—and us—to understand how patriarchy works; likewise, Alice Wexler’s memoir about being at risk for developing Huntington’s disease productively redefines the notion of risk not in terms of fifty-fifty odds of dying or surviving, but rather to inhabit a “third space,” “one that is neither certainty nor complete uncertainty.” (208). Woodward invites us to identify with and “feel” with most of the writers she chooses, and to gain insight from their observations.

A moment ago I asked how shifting focus from medical narratives to financial narratives might alter the structures of feeling we see emerging; I now want to ask after cases in which when bona-fide emotional responses seem not to provide epistemological edge with respect to social experience, but instead foment mystification and distortion. It may be true that a subject like Glenn Beck, in conjunction with Fox News, produces sensation rather than emotion. But we cannot doubt that this sensation is experienced by receptive audiences as real emotion: negative emotions like anger, sadness, depression; or positive ones like solidarity and empowerment. These emotions are real/genuine, and yet they spring from faulty premises. The premises are faulty in that, from my perspective, the anger that hails from a lost sense of racial entitlement is morally and politically unacceptable, but also because they rely upon a proud rejection of sustained analysis (conflation of Keynesian economics with Stalinism, etc). In the face of such distortion and mystification, how are we to avoid the importance of these emotions to the people who are guided by them? Can we assume that no insight comes from these emotions, even if we find their starting premises and assumptions faulty, or even reprehensible?

Return to beginning of post

“Statistical Joy?” Response 2
Written by Jane Desmond (Anthropology/GWS/ International Forum for US Studies)

In this passionately felt and elegantly written book, there are many key strands, or, as Woodward calls them “elastic rubrics” of cultural hypotheses (p.135). She offers this as a text to think with rather than a proclamation of rigid arguments achieved. And this evening, given our shared readings, I want to think with her about just two of them: aging and statistics.

Like all of us here, I am “aging”—the term we give to a bodily persistence of being over time. I am, understandably, and predictably, not as young as I once was. Neither, I suspect, are you. This passage of time and our own persistence in it is, if we are lucky, inevitable. But I am very struck by the historicity of these experiences, as Woodward notes when she carefully delineates the realm of her study as post-1950s, and mostly but not exclusively anchored in U.S. and Western European texts and circumstances. She reminds us that emotions and our experiences of them are historically evoked and culturally made meaningful. And that they explicitly or implicitly shape the life experience—the ways of knowing, being, doing, and feeling, and making publics—of everyone in particular communities of shared belief.

Woodward connects both aging and statistics in our own time and place with notions of a vulnerable body, and proposes the concept of a postmodern “society of the statistic” to go along with Baudrillard’s “society of the spectacle.” Our ceaseless bombardment by probabilities and ratios in realms as disparate as sports and medicine, Woodward argues, can give rise to a pervasive statistical panic—a fear of the future based on an analysis of probability attached to a vulnerable body.

Just a few weeks ago, I had a moment of statistical panic myself—echoing that that Woodward recounts in her introduction—when perusing our local newspaper here, the Champaign, Illinois, News-Gazette. I can look back now and see that its power lay in its melding of aging and risk. Skimming a page, my eye caught on the sharp shard of a title in the business section “Seniors face matrix of misery,” those double “m’s” driving home the point. According to the writer, Scott Burns, “solvent seniors,” (with those hissing double “s”es) that is, those in the broad middle class who had been prudently saving for decades, now faced, due to the collapse of the stock markets, a brutal truth: they may outlive their money. (This truth does not even begin to address the plight of the poor, just the projections of the middle class.) As Woodward noted about these scare articles, it occurred to her at one point that the smart move would be to die now and beat the odds of living too long.

Seniors were not me, of course, they were my mother’s generation, but I had a hunch that, if I played my cards right, and stayed on the good side of the statistics of disease, death by car crash, and avoided accidents in the home while changing light bulbs, I might someday in the not so very inconceivably distant future, pass over that line from the unmarked “adult” category to that of “senior,” finally accruing discounts on the early bird dinner specials, and a membership in the AARP—even here I find myself slipping into the distancing technique of irony—holding at bay the persistence of time—for, I realized, not only do I not want to outlive my money, I do not want to outlive my life.

The notion of “outliving our lives” is telling, and hopefully a productive and provocative one. “Outliving” immediately invokes a sense of loss: loss of dignity, loss of youth, loss of autonomy, loss of loved ones, loss of self recognition, loss of recognition by others, loss of options. We could imagine a different calculus—one based on accrual over time—of friends, of experiences, of skills, of money—but statistical panic feeds on fear of loss. Woodward carefully excavates these fears and their aftermath—grief.

But there is another question we can ask, flipping things around: What other cultural work does this saturation by statistics possibly do? Is there is such a phenomenon as “statistical inoculation,” or “statistical hubris?” If one out of seven women in this country will get cancer, 6 out of 7 won’t. Perhaps there are realms in life where we calculate our odds and come out smiling...perhaps the statistics are weighted toward cohorts not our own: for example, if your odds of X,Y or Z are higher if you smoke, lower if you don’t, better if you are not obese, more probable if you are of, say, African American background, but less likely if you are Latina? and so on, and on.

Do we make continual small calculations, parcing ever more finely our inclusion or exclusion in multiple categories of risk?

Like a pack of sheep tightly meshed together in the face of an attack by wolves, we hope that we will be on the inside of the pack, protected from harm by the insulating presence of so many others, those at higher risk, exposed to the sharp teeth of marauding wolves or in this case, of disease. Do people experience a sense of protection, of ease, of lack of fear based on the idea of “statistical inoculation?”

Part of our statistical panic is the sense that so many of the losses we fear cannot be protected against by whatever social power we may have, or by justice, or by our beliefs, or even by our actions. In most cases, there is little we can do to “make sure” we do not lose ourselves and lose our minds, despite all the Dr. Oz or Oprah advice about doing crossword puzzles and eating our vegetables to prevent Alzheimer’s.

While there are sometimes clear differences in our odds based on social privilege, or poverty, or other unjust differentials, there is also the fact that loss in general is a democratic infection, reaching each of us in turn, but reaching us somewhat differently. So we might ask further who has what kinds of statistical panic? And what roles does it play in their/our lives and the lives of their/our particular communities? How is statistical panic endured or experienced differentially?

Finally there is the opposite of statistical panic—statistical joy!—the joy associated with “beating the odds.” This is what winning the lottery is all about. Or, in our academic profession, this might refer to the accomplishment of actually getting a job in a market saturated by Ph.D.s. We could call this the emotional high of “hitting the jackpot!”—where the sweetness of success, or of a positive outcome, is so heightened by our awareness of its unlikely probability that we experience a frisson of joy tied to the palimpsest of dread.

So, while we may experience statistical panic, we may also actively engage the inoculatory or jackpot effects of statistical living—of calculating our effects, and affects, against a cascading wall of prediction and fears for the future—of statistical panic, statistical relief, and statistical joy.

In all of these we remain embedded in the notion of a world supposedly graspable by a calculus of probability, hoping against hope that we have a chance of escaping death, of winning the jackpot, of being the sheep safe at the inner circle of the pack, of being the one thrust into the winner’s spotlight, of—against all odds—being safe, even flourishing, in an unpredictable future. Statistics raise the flag of danger and the relief of escape, the hubris of “not me” in a world of “why not you?” Kathleen Woodward spurs us to think about these ways of projecting fear, determining actions, narrating lives, encountering loss, and imagining the future, and of considering what may be the grounds for hope and change.

Return to beginning of post

Perspectives on Statistical Panic: Response 3
Written by Elizabeth Massa Hoiem (English)

Statistical Panic examines the dynamic landscape of emotional experience in 20th-century American culture, using narratives to demonstrate how personal emotions are culturally inflected and social emotions are subjectively embodied. Focusing on autobiography and emotional pairs—such as the oscillating boredom and rage that constitute statistical panic—Kathleen Woodward confesses her debt to Freud, while historicizing the relationship between narrative and emotions. Whereas the goal of psychoanalysis in the early 20th century was to discover emotions hidden within us and use narration to release them, feminist activists in the later 20th century formed communities around personal narratives of collectively experienced anger. In postmodern cultures, plagued by emotional poverty and overstimulation, the task is to recover emotions. Narrating emotional experiences helps mediate intensities and revive shared physiological emotions like grief—it is a modern talking-cure that revitalizes our emotional life.

I find myself intrigued by Prof. Woodward’s methodology, which creates nested layers of self-reflection. Statistical Panic analyzes memoirs as supporting evidence, examines how we analyze self-reflecting narratives or use them as cures, and it invites readers to participate by recalling their emotional experiences as test-cases. Reading Statistical Panic demands that we examine the speculative “cultural hypotheses” that it puts forward about grief, anger, beaurocratic rage, and statistical panic through our personal experiences of these emotions. By integrating analysis and story-telling, and by inviting readers to do likewise, Statistical Panic disrupts what Woodward calls “professional cool,” an overreliance on measured argument pervasive in academic writing, which is itself a symptom of postmodern flattening of affect.

In her introduction, she reminds her readers, like the graduates in her seminars: “We all have experience of the emotions and shouldn’t hesitate to draw on it—reflecting on it, turning it over in our minds, watching when a certain emotion subsides and is replaced by another, and placing it in perspective in the arc of our own personal lives and in the context of social constraints, commands, and controls as well as larger historical change.” With what space remains, therefore, I would like to offer my reflections on how I experience the “equal opportunity emotion” of statistical panic, keeping in mind Woodward’s insistence that psychological emotions can originate in social interactions or create the basis for shared communities.

As I reflected on when I’ve felt statistical panic in the last few months, one dominating instance involved statistics that do not claim to represent me. The examples of medical statistical panic that Woodward selects describe people who feel personally represented by the statistics that haunted them. And we identify with these accounts because we, too, have bodies vulnerable to illness. I find, however, that I have strong emotional reactions to statistics, even when I am removed from the represented group. In particular, I recently had a strong emotional reaction to hearing that close to 1/3 of women veterans say they were sexually assaulted during their service, that 80-90% of sexual assaults go unreported in the military, and of those reported, only 1.6% end in both conviction and dishonorable discharge for the offender. I remain deeply disturbed by these numbers, even though I am not and will not be in the military, nor do I have female friends in the service. How do we respond to statistics like these, which represent other groups of people that have quite different experiences from ourselves? Do such statistics remain intensities, or can we experience them emotionally? With these questions, I draw upon Woodward’s analysis of liberal sympathy, which she approaches with skepticism, but ultimately finds more compelling than compassionate conservatism because it recognizes of the embodied experiences of actual suffering persons. I ask these questions because activism partially relies on other people caring about statistics that may not directly represent their own risk. I am concerned that in managing risk, we sometimes care very little about the risk of others, and that a lack of shared risk helps perpetuate injustices that disproportionately affect only one segment of the human population. The US government’s use of robotic warfare is only one instance in which minimizing risk to one group, American soldiers, makes war more palatable by ignoring the risk to another group, civilians living in war zones.

Another kind of statistics—those related to higher education—deeply affect most of the people I know. I’ll hint at just two of many possible topics where I suspect we may feel statistical panic, collectively. First, the statistical panic of public funding: In 1980, 44.5% of the budget for the University of Illinois at Urbana-Champaign was funded by state taxes, compared with 16.4% of funding that now comes from the state. We are all aware of the barrage of statistics associated with state funding, concerning salaries, undergraduate tuition hikes, and the racial and economic diversity of our student population. And second, graduate students in our profession live in a constant state of statistical panic when applying for jobs. Inside Higher Education reported last December that we should expect a 35% drop in positions this year, which means a 51% drop in total over the last 2 years, arriving at a historic low. Only half of these jobs will be for tenure-track positions. Our response, as students, to these statistics is personal to the point of atomizing: I must work harder at my job application materials; I must consider alternative employment outside of the academy; I must not be the one who succumbs to risk. A personal risk management response to statistics that affect a group can reinforce the problem at hand by making it a matter of personal responsibility. It is my fault if I do not get a tenure-track job, even though the lack of tenure-track jobs is systemic. Can statistical panic be used, instead, to form communities that share risk?

Return to beginning of post


Make A Comment