Cross-posted at Cyborgology.

Fake news among the alt-right has been central in post-election public discourse, like with Donald Trump’s dubiously sourced tweet about the “millions of illegal voters” supposedly driving Clinton’s substantial lead in the popular vote. Less attention, however, has been paid to the way “real” news is, to use the sociologist Nathan Jurgenson’s term, based in “factiness,” described as “the feel and aesthetic of ‘facts,’ often at the expense of missing the truth.”  Mainstream news gets cast as objective in part because journalists, stack of papers and obligatory pen studiously in hand, point to statistics that back up their reports. Such reliance on “data” can mask the way that humans are involved in turning things into numbers and numbers into stories. So here I present a cautionary tale.

It is a common truism that white male voters without college degrees disproportionately supported Trump in the 2016 election. Indeed, the notion that men with high school as their highest level of education were more likely to vote for Trump is an empirically supported fact. This data point spread widely throughout the campaign season, and bore out in the post-election analyses. But also in the post-election analyses — over which researchers poured in response to the statistically surprising result — another data point emerged that could have, but didn’t, change the narrative around this demographic voting bloc.

The data point that emerged was that white American men without college degrees have remained economically depressed since the 2008 recession and subsequent recovery. Although the U.S. economy has been steadily improving, the economic reality for this particular segment of the population has not. This is what Michael Moore talked about experientially (but not statistically), claiming that he knows the people who live in the rust belt, and they are struggling. He was right, the data show that they are struggling. Highlighting the economic reality for people without college degrees in the U.S. tells a very different story than highlighting the fact that they don’t have college degrees. The former renders an image of a voting contingent who, in the face of personal economic hardship that contrasts with national economic gain, are frustrated and eager to try something — anything — new. The latter renders an image of ignorance.

Data about education levels of voters is transformed by its coupling with economic trajectories. What’s been strange, is that although this coupling was discovered, it never really penetrated the larger “what happened” narrative. This is particularly strange given the meticulous and sometimes frantic search for explanation and the media’s public introspective quests to understand how so many got it all so wrong.

The transformative effect of the economic data point and its failure to effectively transform the story underlines two related things: data are not self-evident and narrative currents are hard to change.

The data weren’t wrong — people without college degrees were more likely to vote for Trump — but they were incomplete and in their partialness, quite misleading. That’s not a data problem, it’s a people problem. Data are not silent, but they are inarticulate. Data make noise, but people have to weave that noise into a story. The weaving process begins with survey construction, and culminates in analyses and reports. Far from an objective process, turning data into narrative entails nuanced decisions about the relevance of, and relationship between, quantifiable items captured through human-created measures. The data story is thus always value-laden and teeming with explicit and implicit assumptions.

Framing a contingent of Trump supporters through the exclusive metric of education without examining the interaction, mediating, and moderating effects of economic gains, was an intellectual decision bore out through statistical analyses. That is, pollsters, strategists, and commentators treated “lack of education” as the variable with key explanatory power. Other characteristics or experiences of those with low levels of education could/should/would be irrelevant.

Such dismissal created a major problem with regard to Democratic strategy. To situate a voting bloc as “uneducated” is to dismiss that voting bloc. How does one campaign to those voting in ignorance? In contrast, to situate a voting bloc as connected through an economic plight not only validates their position, but also gives a clear policy platform on which to speak.

But okay, after the election, analysts briefly shed light on the way that economics and education operated together to predict candidate preference. Why has this gotten so little attention? Why is education — rather than economics or the economic-education combination — still the predominant story?

The predominance of education remains because narrative currents are strong. Even when tied to newly emergent data, established stories are resistant to change. Narratives are embedded with social frameworks, and changing the story entails changing the view of reality. A key tenet of sociology is that people tend towards stability. Once they understand and engage the world in a particular way, they do social and psychological gymnastics to continue understanding and engaging the world in that way. To reframe (some) Trump voters as part of an economic interest group that has been recently underserved, is an upheaval of previous logics. Moreover, disrupting existing logics in this way forces those who practice those logics to, perhaps, reframe themselves, and do so in a way that is not entirely flattering or identity affirming. To switch from a frame of ignorance to a frame of economics is to acknowledge not only that the first frame was distorted, but also, to acknowledge that getting it wrong necessarily entailed ignoring the economic inequality that progressives take pride in caring so much about. Switching from ignorance to economics entails both a change in logic and also, a threat to sense of self.

Data are rich material from which stories are formed, and they are not objective. Tracing data is a process of deconstructing the stories that make up our truths — how those stories take shape, evolve, and solidify into fact. The “truth” about Trump voters is of course complex and highly variable. The perpetually missed nuances tell as much of a story as those on which predominant narratives hang.

Jenny L. Davis, PhD, is in the department of sociology at James Madison University. She studies social psychology, experimental research methods, and new and social media. She is also a contributing author and editor at Cyborgology.  You can follow her at @Jenny_L_Davis.

Sometimes there’s nothing to do but take matters into our own hands. Danielle Lindemann, a mother and sociologist, decided to do just that. After discovering that one of her daughter’s books required some “subversion,” she decided to do a little editing. Here’s to one way of fighting the disempowering messages taught to little girls by capitalist icons:

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Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.

No matter which way you voted or who wins, today will go down in history as the first time a woman either won or lost the presidency of the United States. Today, in a contemplative mood, I turned back to the chapter on politics I wrote with Myra Marx Ferree for our sociology of gender book. It’s an ode to the suffragist with a final paragraph that resonates very, very strongly on this day. Read, and let the reverberations of history stir your soul.

— Lisa

***

In 1848 a small group of American women made the decision to seek suffrage, the right to vote. For most of modern history, governments did not allow women this right, nor the other rights and responsibilities of citizenship—to serve on juries, give legal testimony, or hold public office—and American women were no exception. Many thought the idea was impossible, dangerous, even laughable. Opponents mocked suffragists, suggesting that giving women the vote was as ridiculous as giving it to housecats.

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The fight for suffrage was not won quickly or easily and many suffragists died of old age before they could see their efforts realized. In addition to ridicule, suffragists faced government repression and violence. Most suffragists were peaceful, but some weren’t above aggression themselves. One group in the United Kingdom set buildings on fire and learned jujitsu to defend themselves from the police. Over 1,000 suffragists would be imprisoned in the United Kingdom and United States. There they endured brutal force-feeding after initiating hunger strikes that endangered their lives.

The fight for suffrage involved both inspiring coalitions and ugly divides. Many suffragists were abolitionists first, activists in the fight against human slavery. White and black men and women worked side-by-side for this hard-won victory. After slavery was abolished in 1865 and black men were granted suffrage in 1869, black women continued to fight valiantly for their own vote. As abolitionist Sojourner Truth observed: “If colored men get their rights, and colored women not theirs, the colored men will be masters over the women, and it will be just as bad as it was before.”

White suffragists often disagreed on whether their efforts should benefit all women or only white women. Anti-suffrage activists tapped into widespread animosity toward black people, reminding a racist public that women’s suffrage would not only put women into the voting booth, it would double the black vote. Some suffragist groups were themselves racist, excluding black women from their organizations, activities, or platform. Many black women started suffrage organizations of their own.

Eventually, suffragists began making alliances with women in other countries. By the early 1900s, this international women’s organizing had begun to shift public opinion in their favor. Finland and New Zealand were the first to grant women the right to vote in the 1910s. The United States came around in 1920, giving suffrage to both black and white women together. By then the movement was rolling across the globe. In less than thirty years, women’s suffrage became a global norm. The last state to disallow women’s voting, Saudi Arabia, allowed them to vote in 2015.

Today universal suffrage, the right of all citizens to vote, is the very definition of democracy. This right is taken for granted today, so much so that many people don’t even know the word anymore. In the 1800s, however, it was a wholly radical claim, defined as an idea that doesn’t (yet) resonate with most members of a population. In fact, it was a massively important step toward dismantling political systems that recognized some people as full citizens but not others. It was also extraordinarily disruptive to the social order and the distribution of power. It is a testament to the fact that, even when social conditions are stubbornly entrenched and defended by powerful people, change—even radical change—is possible.

Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.

Myra Marx Ferree, PhD is a professor at the University of Wisconsin, Madison. She is the recipient of numerous prizes for contributions to gender studies and does research on global gender politics. Among her many books is a textbook on the sociology of gender , with Lisa Wade.

In a recent poll of registered voters by Pew Research Center, 30% of women, 26% of people of Hispanic descent, and 2% of black people say they’re planning to vote for Donald Trump. In fact, polls consistently find that women and racial minorities favor Hillary Clinton. So, what do we make of the statistics-defying members of those groups who support Trump?

Flickr photo by Johnny Silvercloud; creative commons license.

Flickr photo by Johnny Silvercloud; creative commons license.

For many, this fact is source of cognitive dissonance, that uncomfortable feeling of knowingly holding irreconcilable beliefs. How could women, racial minorities, and especially minorities who are women, support a man who so persistently insults and attacks them? The discomfort of dissonance has led some to look for answers, with a few coming to the conclusion that supporting Trump is equivalent to betrayal — an identity-voiding decision (“You’re not true Mexican“) — and that women and racial minorities who support Trump are “hypocritical” and “ought to be ashamed.”

This sense of cognitive dissonance though, the idea that it’s “strange” for women or racial minorities to support Trump, is based on identity politics. Such politics has its strengths, but it also risks reducing complex social beings into one-dimensional labels, with the assumption that the label is the most important thing about them.  In this case, critics of women and racial minorities for Trump find their support of him to be more incomprehensible than that of others, based on identity alone. Thus, the individual blurs into a monolithic group, where each person is expected to be politically identical to the whole, thereby setting up the case for Trump support to be framed as a betrayal.

In fact, people are complex. They carry many intersecting identities at once, sometimes ones with conflicting politics attached, as well as a suite of other personal characteristics and structural situations. People make political choices that seem to contradict some of their identities not because they’re hypocrites, but because most people are themselves a whole host of contradictions. Reality is never so clear cut and finite as a singular label, nor are humans so easily generalized.

Given these realities, the poll numbers with which I began this post makes some sense. Trump has insulted and degraded women and minorities, and he has made policy promises that threaten them, too. Based on these facts, it should be no surprise that he is losing large swaths of those groups to Clinton. But given the complexity of identity, it should also be no surprise that he isn’t losing all of them. People are complicated, and politics is as well.

Paige Miller is a graduate student at the University of New Orleans working on her MA in Sociology. Her research interests include social psychology, new media, gender, and inequalities. You can find her on Twitter and Instagram.

TW: racism  and sexual violence; originally posted at Family Inequality.

I’ve been putting off writing this post because I wanted to do more justice both to the history of the Black-men-raping-White-women charge and the survey methods questions. Instead I’m just going to lay this here and hope it helps someone who is more engaged than I am at the moment. I’m sorry this post isn’t higher quality.

Obviously, this post includes extremely racist and misogynist content, which I am showing you to explain why it’s bad.

This is about this very racist meme, which is extremely popular among extreme racists.

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The modern racist uses statistics, data, and even math. They use citations. And I think it takes actually engaging with this stuff to stop it (this is untested, though, as I have no real evidence that facts help). That means anti-racists need to learn some demography and survey methods, and practice them in public. I was prompted to finally write on this by a David Duke video streamed on Facebook, in which he used exaggerated versions of these numbers, and the good Samaritans arguing with him did not really know how to respond.

For completely inadequate context: For a very long time, Black men raping White women has been White supremacists’ single favorite thing. This was the most common justification for lynching, and for many of the legal executions of Black men throughout the 20th century. From 1930 to 1994 there were 455 people executed for rape in the U.S., and 89% of them were Black (from the 1996 Statistical Abstract):

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For some people, this is all they need to know about how bad the problem of Blacks raping Whites is. For better informed people, it’s the basis for a great lesson in how the actions of the justice system are not good measures of the crimes it’s supposed to address.

Good data gone wrong

Which is one reason the government collects the National Crime Victimization Survey (NCVS), a large sample survey of about 90,000 households with 160,000 people. In it they ask about crimes against the people surveyed, and the answers the survey yields are usually pretty different from what’s in the crime report statistics – and even further from the statistics on things like convictions and incarceration. It’s supposed to be a survey of crime as experienced, not as reported or punished.

It’s an important survey that yields a lot of good information. But in this case the Bureau of Justice Statistics is doing a serious disservice in the way they are reporting the results, and they should do something about it. I hope they will consider it.

Like many surveys, the NCVS is weighted to produce estimates that are supposed to reflect the general population. In a nutshell, that means, for example, that they treat each of the 158,000 people (over age 12) covered in 2014 as about 1,700 people. So if one person said, “I was raped,” they would say, “1700 people in the US say they were raped.” This is how sampling works. In fact, they tweak it much more than that, to make the numbers add up according to population distributions of variables like age, sex, race, and region – and non-response, so that if a certain group (say Black women) has a low response rate, their responses get goosed even more. This is reasonable and good, but it requires care in reporting to the general public.

So, how is the Bureau of Justice Statistics’ (BJS) reporting method contributing to the racist meme above? The racists love to cite Table 42 of this report, which last came out for the 2008 survey. This is the source for David Duke’s rant, and the many, many memes about this. The results of Google image search gives you a sense of how many websites are distributing this:

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Here is Table 42, with my explanation below:

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What this shows is that, based on their sample, BJS extrapolates an estimate of 117,640 White women who say they were sexually assaulted, or threatened with sexual assault, in 2008 (in the red box). Of those, 16.4% described their assailant as Black (the blue highlight). That works out to 19,293 White women sexually assaulted or threatened by Black men in one year – White supremacists do math. In the 2005 version of the table these numbers were 111,490 and 33.6%, for 37,460 White women sexually assaulted or threatened by Black men, or:

everyday

Now, go back to the structure of the survey. If each respondent in the survey counts for about 1,700 people, then the survey in 2008 would have found 69 White women who were sexually assaulted or threatened, 11 of whom said their assailant was Black (117,640/1,700). Actually, though, we know it was less than 11, because the asterisk on the table takes you to the footnote below which says it was based on 10 or fewer sample cases. In comparison, the survey may have found 27 Black women who said they were sexually assaulted or threatened (46,580/1,700), none of whom said their attacker was White, which is why the second blue box shows 0.0. However, it actually looks like the weights are bigger for Black women, because the figure for the percentage assaulted or threatened by Black attackers, 74.8%, has the asterisk that indicates 10 or fewer cases. If there were 27 Black women in this category, then 74.8% of them would be 20. So this whole Black women victim sample might be as little as 13, with bigger weights applied (because, say, Black women had a lower response rate). If in fact Black women are just as likely to be attacked or assaulted by White men as the reverse, 16%, you might only expect 2 of those 13 to be White, and so finding a sample 0 is not very surprising. The actual weighting scheme is clearly much more complicated, and I don’t know the unweighted counts, as they are not reported here (and I didn’t analyze the individual-level data).

I can’t believe we’re talking about this. The most important bottom line is that the BJS should not report extrapolations to the whole population from samples this small. These population numbers should not be on this table. At best these numbers are estimated with very large standard errors. (Using a standard confident interval calculator, that 16% of White women, based on a sample of 69, yields a confidence interval of +/- 9%.) It’s irresponsible, and it’s inadvertently (I assume) feeding White supremacist propaganda.

Rape and sexual assault are very disturbingly common, although not as common as they were a few decades ago, by conventional measures. But it’s a big country, and I don’t doubt lots of Black men sexual assault or threaten White women, and that White men sexually assault or threaten Black women a lot, too – certainly more than never. If we knew the true numbers, they would be bad. But we don’t.

A couple more issues to consider. Most sexual assault happens within relationships, and Black women have interracial relationships at very low rates. In round numbers (based on marriages), 2% of White women are with Black men, and 5% of Black women are with White men, which – because of population sizes – means there are more than twice as many couples with Black-man/White-woman than the reverse. At very small sample sizes, this matters a lot. But we would expect there to be more Black-White rape than the reverse based on this pattern alone. Consider further that the NCVS is a householdsample, which means that if any Black women are sexually assaulted by White men in prison, it wouldn’t be included. Based on a 2011-2012 survey of prison and jail inmates, 3,500 women per year are the victim of staff sexual misconduct, and Black women inmates were about 50% more likely to report this than White women. So I’m guessing the true number of Black women sexually assaulted by White men is somewhat greater than zero, and that’s just in prisons and jails.

The BJS seems to have stopped releasing this form of the report, with Table 42, maybe because of this kind of problem, which would be great. In that case they just need to put out a statement clarifying and correcting the old reports – which they should still do, because they are out there. (The more recent reports are skimpier, and don’t get into this much detail [e.g., 2014] – and their custom table tool doesn’t allow you to specify the perceived race of the offender).

So, next time you’re arguing with David Duke, the simplest response to this is that the numbers he’s talking about are based on very small samples, and the asterisk means he shouldn’t use the number. The racists won’t take your advice, but it’s good for everyone else to know.

Philip N. Cohen is a professor of sociology at the University of Maryland, College Park. He writes the blog Family Inequality and is the author of The Family: Diversity, Inequality, and Social Change. You can follow him on Twitter or Facebook.

Flashback Friday.

Previously marketed to women, skin lightening, bleaching, and “fairness” creams are being newly marketed to men.  The introduction of a Facebook application has triggered a wave of commentary among American journalists and bloggers.  The application, launched by Vaseline and aimed at men in India, smoothes out blotches and lightens the overall skin color of your profile photo, allowing men to present a more “radiant” face to their friends.

The U.S. commentary involves a great deal of hand-wringing over Indian preference for light skin and the lengths to which even men will go to get a few shades lighter.  Indians, it is claimed, have a preference for light skin because skin color and caste are connected in the Indian imagination.  Dating and career success, they say further, are linked to skin color.  Perhaps, these sources admit, colorism in India is related to British colonialism and the importation of a color-based hierarchy; but that was then and, today, India embraces prejudice against dark-skinned people, thereby creating a market for these unsavory products.

The obsession with light skin, however, cannot be solely blamed on insecure individuals or a now internalized colorism imported from elsewhere a long time ago.  Instead, a preference for white skin is being cultivated, today, by corporations seeking profit.  Sociologist Evelyn Nakano Glenn documents the global business of skin lightening in her article, Yearning for Lightness.  She argues that interest in the products is rising, especially in places where “…the influence of Western capitalism and culture are most prominent.”  The success of these products, then, “cannot be seen as simply a legacy of colonialism.”  Instead, it is being actively produced by giant multinational companies today.

The Facebook application is one example of this phenomenon.  It does not simply reflect an interest in lighter skin; it very deliberately tells users that they need to “be prepared” to make a first impression and makes it very clear that skin blotches and overall darkness is undesirable and smooth, light-colored skin is ideal.  Marketing for skin lightening products not only suggests that light skin is more attractive, it also links light skin to career success, overall upward mobility, and Westernization.  Some advertising, for example, overtly links dark skin with saris and unemployment for women, while linking light skin with Western clothes and a career.

The desire for light skin, then, isn’t an “Indian problem” for which they should be entirely blamed. It is being encouraged by corporations who stand to profit from color-based anxieties that are overtly tied to the supposed superiority of Western culture.  These corporations, it stands to be noted, are not Indian.  They are largely Western: L’Oreal and Unilever are two of the biggest companies.  The supposedly Indian preference for light skin, then, is being stoked and manufactured by companies based in countries populated primarily by light-skinned people.  As Glenn explains, “Such advertisements can be seen as not simply responding to a preexisting need but actually creating a need by depicting having dark skin as a painful and depressing experience.”

Before pitying Indian seekers of light-skin, condemning the nation for colorism, or gently shaking our heads over the legacies of colonialism, we should consider how ongoing Western cultural dominance (that is, racism and colorism in the West today) and capitalist economic penetration (that is, profit through the cultivation of insecurities around the world) contributes to the global market in skin lightening products.

Originally posted in 2010; crossposted at BlogHer.

Lisa Wade, PhD is a professor at Occidental College. She is the author of American Hookup, a book about college sexual culture, and a textbook about gender. You can follow her on Twitter, Facebook, and Instagram.

Flashback Friday.

Eden H. sent in an exploratory study about kids’ stereotypes of scientists. The U.S. Department of Energy’s Fermilab asked 7th graders to draw and describe a “scientist” before and after visiting the lab on a class trip. They first read about the Fermilab, then came to the lab and meet with some of the scientists and talk about their work. From the Fermilab website:

What we changed for this field trip was the before and after descriptions and small group sessions for each student to meet with two of three physicists rather than one large group session. We deliberately chose a typical white male, a young female and an African American physicist. We let the students and physicist take their discussion where they wanted.

Here are some of the before-and-after pictures and descriptions (all 31 are available here):

In general, the students seemed to come away with an idea of scientists as being more like “normal” people, not just stereotypical geeks in lab coats. But some of the other changes are interesting, too. The author of a post about the study at Restructure! analyzed the before-and-after images (as best as she could identify the sex of the drawings):

  • Among girls (14 in total), 36% portrayed a female scientist in the “before” drawing, and 57% portrayed a female scientist in the “after” drawing.
  • Among boys (17 in total), 100% portrayed a male scientist in the “before” drawing, and 100% portrayed a male scientist in the “after” drawing.

I looked through all of them and only saw one instance (posted above) where the child changed the scientists to be clearly non-White.

Of course this is a small sample, but the results seem to reproduce what other studies have found regarding the importance of role models and gender stereotyping, in particular, that girls are more likely to imagine themselves  in careers when they see women doing them. For instance, the relative lack of female professors in male-dominated departments such as engineering may play a role in discouraging women from choosing to major in such fields (as well as other factors such as steering, concerns about family/work conflicts, etc.).

Originally posted in 2010.

Gwen Sharp, PhD is a professor of sociology and the Associate Dean of liberal arts and sciences at Nevada State College. 

In 1985, Zeneca Pharmaceuticals (now AstraZeneca) declared October “National Breast Cancer Awareness Month.” Their original campaign promoted mammography screenings and self-breast exams, as well as aided fundraising efforts for breast cancer related research.  The month continues with the same goals, and is still supported by AstraZeneca, in addition to many other organizations, most notably the American Cancer Society.

The now ubiquitous pink ribbons were pinned onto the cause, when the Susan G. Komen Breast Cancer Foundation distributed them at a New York City fundraising event in 1991. The following year, 1.5 million Estée Lauder  cosmetic customers received the promotional reminder, along with an informational card about breast self-exams. Although now a well-known symbol, the ribbons elide a less well-known history of Breast Cancer Awareness co-opting grassroots’ organizing and activism targeting women’s health and breast cancer prevention.

The “awareness” campaign also opened the floodgates for other companies to capitalize on the disease. For example, Avon, New Balance, and Yoplait have sold jewelry, athletic shoes, and yogurt, respectively, using the pink ribbon as a logo, while KitchenAid still markets a product line called “Cook for the Cure” that includes pink stand mixers, food processors, and cooking accessories, items which the company first started selling in 2001.  Not to be left out, Smith and Wesson, Taurus, Federal, and Bersa, among other companies, have sold firearms with pink grips and/or finishing, pink gun-cases, and even pink ammo with the pink ribbon symbol emblazoned on the packaging. Because breast cancer can be promoted in corporate-friendly ways and lacks the stigma associated with other diseases, like HIV/AIDS, these companies and others, have been willing to endorse Breast Cancer Awareness Month and, in some cases, donate proceeds from their merchandise to support research affiliated with the disease.

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Yet companies’ willingness to profit from the cause has also served to commodify breast cancer, and to support what sociologist Gayle Sulik calls “pink ribbon culture.” As Sulik notes, marking breast cancer with the color pink not only feminizes the disease, but also reinforces gendered expectations about how women are “supposed” to react to and cope with the illness, claims also corroborated by my own research on breast cancer support groups.

Based on participant observation of four support groups and in-depth interviews with participants, I have documented how breast cancer patients are expected to present a feminine self, and to also be positive and upbeat, despite the pain and suffering they endure as a result of being ill. The women in the study, for example, spent considerable time and attention on their physical appearance, working to present a traditionally feminine self, even while recovering from surgical procedures and debilitating therapies, such as chemotherapy and radiation. Similarly, members of the groups frequently joked about their bodies, especially in sexualized ways, making light of the physical disfigurement resulting from their disease. Like the compensatory femininity in which they engaged, laughing about their plight seemed to assuage some of the emotional pain that they experienced.  However, the coping strategies reinforced traditional standards of beauty and also prevented members of the groups from expressing anger or bitterness, feelings that would have been justifiable, but seen as (largely) culturally inappropriate because they were women.

Even when they recovered physically from the disease, the women were not immune to the effects of the “pink ribbon culture,” as other work from the study demonstrates. Many group participants, for instance, reported that friends and family were often less than sympathetic when they expressed uncertainty about the future and/or discontent about what they had been through.  As “survivors,” they were expected to be strong, positive, and upbeat, not fearful or anxious, or too willing to complain about the aftermath of their disease. The women thus learned to cover their uncomfortable emotions with a veneer of strength and courage. This too helps to illustrate how the “pink ribbon culture,” which celebrates survivors and survivorhood, limits the range of emotions that women who have had breast cancer are able to express. It also demonstrates how the myopic focus on survivors detracts attention from the over 40,000 women who die from breast cancer each year in the United States, as well as from the environmental causes of the disease.

Such findings should give pause. If October is truly a time to bring awareness to breast cancer and the women affected by it, we need to acknowledge the pain and suffering associated with the disease and resist the “pink ribbon culture” that contributes to it.

Jacqueline Clark, PhD is an Associate Professor of Sociology and Chair of the Sociology and Anthropology Department at Ripon College. Her research focuses on inequalities, the sociology of health and illness, and the sociology of jobs, work, and organizations.