David Peterson (Northwestern) spoke with Natasha Myers, Associate Professor of Anthropology at York University and winner of the 2016 Robert K. Merton Book Award for Rendering Life Molecular: Models, Modelers, and Excitable Matter (Duke University Press, 2015). In the interview, Professor Myers discussed theoretical innovations and the next directions of her work.

David Peterson: What is the thesis of your book?

Natasha Myers: This ethnography develops new methods in sensory anthropology to show that that science is more and other than what we have long thought it was. It tracks the life science researchers who model the molecular substructure of living bodies, and documents in vivid detail the embodied, sensory, affective, performative, and aesthetic dimensions of scientific practice and pedagogy. The book takes readers into laboratories and classrooms where practitioners in the arts of molecular modeling go to great lengths to cultivate their skills, and to teach others how to see, feel, imagine, and know what they know about the molecular realm. A central claim of the book is that while these researchers publicly avow mechanistic approaches to the sciences of life, relying heavily on machinic metaphors to describe molecular forms and interactions in the texts they publish, close ethnographic attention to the ways they animate molecular life through stories, and through their articulate movements and gestures, shows that more often than not, practitioners deviate from these conventional scripts. Indeed, by documenting renderings of molecular life that waver between the machinic and the lively, this book shows that mechanism, even in twenty-first century life science, has failed to fully disenchant living matter. Asking “What is life becoming in modelers’ hands?” this book amplifies an otherwise muted liveliness inflecting mechanistic accounts of the stuff of life. In their hands, living matter becomes excitable.

Peterson: How do you see this book contributing to studies in feminist technoscience?

Myers: This book takes inspiration from works by Donna Haraway (1991, 1997), Lucy Suchman (2007), Karen Barad (2007), and many other scholars who develop feminist and queer methodologies to examine forms of performativity, affect, agency, embodiment, and objectivity in science. Feminist technoscience is also particularly attuned to the fraught relations between power and knowledge, and between epistemology and ontology, and these are also prominent themes in the book. One of the primary ways Rendering Life Molecular contributes to this literature is by documenting a group of scientists whose practice of objectivity closely resembles Haraway’s (1988) articulation of “situated knowledges.” These molecular modelers acknowledge and even celebrate the profound contributions they make to producing and securing robust visual facts, and they accentuate, rather than disavow, the role embodied knowledge plays in this process. Indeed, for them, objectivity is measured not by their efforts to detach themselves from their objects, or through forms of automation that would keep their subjectivity at bay; but rather, by their willingness to give themselves over to the laborious process of model building, and allow their objects to inform and transform how they see, feel, and know the molecular realm. This book tunes into the stories scientists tell about their intimate relations with their objects of study, and hitches a ride on scientists’ gestures and movements in order to document the affective entanglements of inquiry in the life sciences. Where forms of “mechanical objectivity” would disavow these entanglements, molecular modelers insist on accounting for how they know what they know, on the partiality of their knowledge, and on locating their unique contributions to crafting visual facts. In this way, they demonstrate what feminist objectivity might look like in practice.

Peterson: Can you talk a bit about the central metaphor of your book? How did you come to the concept of “rendering”? How did it evolve?

Myers: Rendering is a widely used term in computer modeling to describe the processing of images to make them appear three-dimensional, but it also has much older and wider meanings, such as when it is used to describe the process of giving oneself over to a practice, or defined as the act of inflecting or infusing a quality into some thing. The concept of rendering took shape for me while I grappled with ways to understand both the performativity of visual facts in science, and how the visual cultures of science are simultaneously performance cultures. What I came to see is that the models that these scientists build are more than just representations of the molecular realm. I was finding that when molecular models were treated as representations at the end-stage of model building, they could at best gesture at the probable configurations of atoms in a molecule, and as such they tended to induce significant epistemic anxieties about the limits of scientific vision and the epistemic failures of scientists. When treated as renderings, however, models became not just things that stand in for knowledge or phenomena; they could also be seen as enactments or performances that generate new ways of knowing and things known. By treating models as renderings I could redirect my ethnographic attention to the practices of model building and the ways that modelers’ kinesthetic knowledge and intuitions shape and are shaped by the molecular realm. The concept of rendering could also shed light on the performative effects of visual facts: to engage models as renderings is to insist that they do more than just re-present molecular phenomena. Indeed, these models rend the world in some ways and not others, pulling, bending, and tearing at the world to render life molecular.

Peterson: You develop the notion of “haptic vision” to provide a richer account of how scientists draw on their sensory capacities. Can you discuss how kinesthetic entanglements either undermine or expand traditional notions of objectivity which tend to rely on a much narrower concept of scientific “vision” as that which can be explicitly represented and reproduced?

Myers: The concept of “haptic vision” is not new, but it acquires new significance in light of the challenges that molecular modelers face in their efforts to make the molecular realm visible, tangible and workable. Protein crystallographers and other molecular modelers have no direct visual access to the molecular structures they hope to make visible, tangible, and workable. In order to build a three-dimensional atomic-scale model of a protein molecule, they must enmesh themselves in complex technological prostheses in order to decipher probable structures from the scattered shadows of X-ray diffraction patterns. Model building is a hands on, laborious, and often wayward process, and to date, methods for deciphering molecular structures from diffraction patterns have not been fully automated. As such, modelers must rely extensively on trained intuition, tacit and embodied knowledge, and aesthetic judgment. Building a model is an affectively charged performance that engages a modeler’s entire sensorium. It is in the process of building and manipulating their models that modelers’ perceptions, sensibilities, and dexterities are entrained to molecular forms and movements. As a modeler builds their model onscreen, they simultaneously articulate an embodied model, to such an extent that the richest, most detailed model of their molecule comes to reside in their kinesthetic imagination. In the process, modelers’ bodies become the most articulate proxies for rendering molecular forms and movements. Molecular modeler’s vision is thus profoundly haptic; that is, what they come to see and know is shaped by a synesthetic tangle of touch, movement, kinesthesia, proprioception, imagination, memory, and intuition. Getting to know what molecules “look like” is not a detached, disembodied, or neutral process; it involves practitioners’ learning to palpate imperceptible realms, and cultivate a feel for the molecular realm (cf Keller 1983). Objectivity, for these practitioners, is thus profoundly situated, embodied, and felt, and the most robust visual facts are those that can be enacted through the articulate bodies of expert crystallographers.

Works Cited
Barad, Karen, Meeting the Universe Halfway: Quantum Physics and the Entanglement of Matter and Meaning (Durham: Duke University Press, 2007)

Haraway, Donna J., ‘Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspectives’, Feminist Studies, 14 (1988), 575–99

Haraway, Donna J., Simians, Cyborgs, and Women: The Reinvention of Nature (New York: Routledge, 1991)

Haraway, Donna J., Modest_Witness@Second_Millennium.FemaleMan_Meets_OncoMouse: Feminism and Technoscience (New York: Routledge, 1997)

Keller, Evelyn Fox, A Feeling for the Organism: The Life and Work of Barbara McClintock (New York: W.H. Freeman, 1983)

Suchman, Lucy, Human-Machine Reconfigurations: Plans and Situated Actions, 2nd Expanded Edition (New York: Cambridge University Press, 2007)

On February 14, 2017, the SKAT Council voted unanimously to adopt the following policy statement. 

Statement of American Sociological Association Section on Science, Knowledge, and Technology (SKAT) Regarding Recent and Future Actions of the Trump Administration and Congress

The free exchange of ideas is a core value of democratic societies and the foundation of research and academic scholarship. In recent weeks, this principle has come under sustained threat by the new Trump Administration. The immigration ban issued by the Administration on 27 January prevents the movement of international students and scholars into the US, undermining the scientific community’s vibrant internationalism and broad commitment to equality. Confirmation of several Cabinet-level appointments threatens a future in which informed public policy is based on the findings of scientific and scholarly research. Similar threats from Administration officials target the well-established need for affordable healthcare for all Americans and a global commitment to reduce the human causes of climate change. Perhaps most concerning of all, these threats are often aimed at the public institutions that ensure open debate and a respect for empirical evidence: the academy, the media, and the judiciary.

We oppose these threats to equity, justice, internationalism, and the collaborative, free exchange of ideas that must underlie democratic decisions. We reaffirm our commitment to the values and practices that sustain and nurture the scholarly pursuit of knowledge and education of the citizenry, as well as citizens of other countries.

The central purpose of SKAT is to promote scholarly research and professional activity relating to sociology, science, knowledge, and technology. Our section’s social responsibility at this critical moment is twofold: to uphold and defend the principles of academic scholarship and to document, through sociological investigation, the Trump Administration’s effects on science, knowledge, and technology and on the broader causes of social equity and justice. These responsibilities are intertwined and inseparable.

To date, our section has encouraged members to prepare essays on the 2016 campaign and post-election environment and post them to our online blog [https://asaskat.com/blog/]. We have also invited members to contribute relevant teaching and research materials to the section website [https://asaskat.com/]. We will continue to develop programmatic actions as opportunities present, and we welcome member suggestions [email skatpubcomm@gmail.com]. We also encourage members to take action together and individually. In the face of these emerging challenges there are many ways to contribute and participate. Please monitor the SKAT website for a listing of online resources.

For the SKAT Council,

Scott Frickel, Chair
Steven Epstein, Past Chair
Alondra Nelson, Chair-Elect

From friend of the section Pablo J. Boczkowski of Northwestern University:

“Every public has its own universe of discourse and…humanly speaking, a fact is only a fact in some universe of discourse.”

Writing those words three quarters of a century before the Oxford Dictionaries named “post-truth” the 2016 word of the year, Robert Park — a former newspaper journalist and one of the founders of the Chicago School of sociology — understood fake news to be an intrinsic element of any information ecology. Long before Mark Zuckerberg started to be treated as a rapacious business man, noted real and fictitious publishers such as William Randolph Hearst and Charles Foster Kane aimed to exploit the commercial potential of fake news, as did others who predated and succeeded them. On top of intentional attempts to distort or misinform, many unintentional mistakes caught by the public — and a suspicion that there might exist more unidentified ones — have further reinforced a certain stance of skepticism among media audiences over the inherent veracity of the news report.

Read the full article.

by Shreeharsh Kelkar, University of California at Berkeley

As the dust settles after Donald Trump’s shocking upset of Hillary Clinton in the US Presidential Election, and we await the long-term fallout, I am left wondering about what “objectivity” in media institutions will—and should—look like in the future in this age of political polarization. How might we—social scientists interested in understanding how knowledge is made credible—use our insights and contribute to this debate about the future of media institutions in the United States?

The United States today is heavily polarized along political lines. As political scientists have shown time and time again, the polity of the United States experienced a realignment after the Civil Rights movement. The two major parties no longer have substantial overlap, if any; they cater to entirely different constituencies. Republicans are the party of managers, evangelicals, and the white working class; Democrats of organized labor, affluent professionals and minorities. The Democrats have a wider tent and therefore more disagreements, but both parties and their constituencies have sorted themselves into competing and opposing positions on a number of vital issues: the size and role of the welfare state, the scope and status of abortion, and the parameters of religion in public life.

This fracture was bound to have some effects on the media ecosystem. As Paul Starr has shown, American media institutions have constructed themselves as independent organizations, free of political bias—partly because their distribution was heavily subsidized by the federal government and partly because they started to rely on advertising as their main source of revenue. This is typically true of some of the largest circulation media institutions: the New York Times, the Washington Post, Time Magazine, Newsweek, the Atlantic Monthly, CBS, NBC, CNN, and others. These institutions produce this objectivity through a variety of practices: separating their business and editorial divisions, keeping fact and opinion separate, and scrupulously reporting (political) conflicts by giving equal coverage to every side. This arrangement worked very well for a pre-polarization age where both political parties presided over coalitions that spanned the ideological spectrum; indeed, it was constitutive of it.

Polarization caused the first crack in this media ecosystem as it led to the creation of new media institutions at the margins (as well as a public that consumed them avidly) that did not adhere to (and indeed, flouted) this form of objectivity, conservative talk radio being a prime example. Internet-enabled business models multiplied and scrambled this effect. The early Internet bloggers, attuned to the age of polarization, despised the he-said-she-said model of media objectivity, which they sometimes characterized as “false equivalence.” Their blog-posts combined both an obsession with facts and an emphasis on their personal, partisan, voice. Blogging has long since become institutionalized with many early bloggers now writing for more established media publications. What has stayed constant is that their model of writing (embodied in outlets like Vox and Talking Points Memo) is attuned to a different model of objectivity: while being obsessed with facts, figures and truth, it proudly spurns the bipartisan style of, say, the NYT or CNN. Facts and opinions are mixed, and every side does not get equal (or similar) coverage.

But perhaps nothing has been more consequential for media institutions than the rise of curatorial “platforms”: the Facebooks and the Googles who remain many Americans’ gateway to the news that they consume. Curiously, Facebook and Google have adopted the same stance of media objectivity even as their role in guiding public discourse has increased: they stress that they are non-political arbiters of political discourse. They have invested their organizational identity into becoming “platforms”: as platforms, they have no politics and are simply channeling the voice of the users. As Tarleton Gillespie has argued, the word “platform” sometimes refers to “technical platforms, sometimes as platforms from which to speak, sometimes as platforms of opportunity. Whatever tensions exist in serving all of these constituencies are carefully elided.” Unlike media institutions who maintained their objectivity through specific organizing practices like separating fact from opinion, the platforms’ main justification is that they use algorithms. In their telling, the mechanical objectivity of algorithms—and the relative absence of human judgment in this process—is the reason their curatorial decisions are objective.

Why have Facebook and Google studiously resisted being styled as media institutions and stuck to their guns in calling themselves mere platforms? A couple of reasons are clear: their reliance on advertising for revenue, and the fact that, in this age of polarization, being labeled “political” turns away people of the opposite political affiliation. But there is a third, perhaps more insidious, reason. Facebook and Google are committed to the principle of what has been called “context collapse“: Google wants to index all the information in the world and Facebook wants to make all activities “social” all the way down. These aspirations are sweeping in that they seek to dismantle the boundaries between activities such that everything is mediated through these platforms; the distinctions between the social and the commercial, the personal and the public, and the political and the non-political are blurred. To slightly twist a phrase coined by Helen Nissenbaum, platforms seek to blur, even exterminate, the “contextual integrity” of particular activities so that they all start to be mediated by the technological machinery that these platforms specialize in. Expanding their activities to cover more and more domains is the key to Facebook and Google’s Silicon Valley-inspired business models. Explicitly regulating content or regulating content-producers is not conducive to the growth of these platforms.

To understand this, consider the dispute over Facebook Trends, and the current debate about “fake news.” In this age of polarization, how then do we restore a meaningful public sphere of reasonable political debates?

Facebook Trends, Fake News and Objectivity

After Trump’s victory, an increasing amount of liberal dismay focused on the rise of “fake news“: transparently false and outrageous claims about Hillary Clinton, manufactured sometimes in Macedonia, at other times in California (and in a demonstration, that sometimes commerce knows no politics, by gung-ho entrepreneurial Democrats!), that managed to nonetheless circulate widely among conservative audiences primarily through sharing on Facebook. Critics alleged that these fake stories circulated more than real stories did, and that this had some role in the election results, and that Facebook should do something about this.

But before fake news, there was Facebook Trends. A few months ago, the website Gizmodo unveiled what seemed to many a scandalous revelation. Facebook’s Trending Topics were not really algorithmically generated; rather they were curated, by a group of people (to be sure, a very small group of people who were neither trained in the practices of journalism, nor paid very well), who worked with what Facebook’s massive programs discovered. Even more damning, this group of people was making choices that systematically deleted conservative news headlines while privileging more liberal ones. Or so alleged the main source for the article: a conservative Trends curator.

Scholars have expressed dismay about what the Trending fracas revealed: first, that the general public sometimes seems unaware that there are people behind the algorithms of Facebook, and second, that Facebook’s Trend curators were abysmally paid employees with little or no formal training in any journalistic enterprise, an indication that Facebook treated a fundamental job as contingent work. Conservatives expressed a different kind of dismay: that Facebook had a liberal bias just like the New York Times and was systematically discriminating against them.

Facebook’s reaction to the controversy was instructive. Conservative luminaries were invited to Facebook’s headquarters to have their concerns registered. And then, Facebook essentially fired its Trending staff and left the algorithms essentially unsupervised. The result has not especially been good, as the Washington Post has shown: the output of the Trends feature has steadily grown more incoherent.

Facebook could have certainly dealt with the Trends controversy in a different way. They could have strengthened the job description of these Trends curators and hired journalists rather than contingent workers. They might have made the process through which a Trend was captured and published transparent (at a similar level of abstraction they use for their much-vaunted Edgerank algorithm so that they revealed no proprietary information). They could have hired more conservative curators and explicitly claimed that their curators were as representative as possible of the general US population. Instead, they opted for an argument where they fell back on the mechanical objectivity of algorithms. This allowed Facebook to remain a neutral, non-political platform, and it seemed to assuage affronted conservatives.

Facebook’s approach to dealing with fake news has been notably different, maybe because influential Facebook employees may have felt unease at their own complicity in the election of Donald Trump. After some initial denials by Mark Zuckerberg, Facebook recently announced that independent fact-checkers would get privileged access to Facebook and would be able to flag egregious articles. Shared Facebook items would thus carry some sort of mark verifying their authenticity. Facebook is also clearly at work on more computational mechanisms to identify false news items. Time will tell whether these methods raise an outcry from conservatives who argue that the fact-checkers are not fair and have some sort of liberal bias.

Rather than falling back and doubling down once again on the objectivity of algorithms, Facebook created what is essentially a political solution to the fake news problem: it outsourced the verification of shared links to third parties who have established practices of adjudicating truth claims by media institutions. Certain issues remain unresolved: what happens when particular parties dispute the judgment of the fact-checkers? How is the judgment of the fact-checkers incorporated into the Edge rank algorithm, given the brute fact that items at the top of the Facebook newsfeed tend to be read the most? Time will tell.

We—and Facebook—might conceivably think of other models of objectivity in our efforts to create trust-worthy media institutions (i.e. trusted by both liberals and conservatives) in an age of polarization and platforms. In her comparison of the American, British and German regulation of biotechnology, Sheila Jasanoff characterizes each national regulatory style as “contentious,” “communitarian,” and “consensus-seeking” respectively. In the German polity, for example, she finds an emphasis on the representativeness of knowledge-making bodies, while the United States hopes to resolve regulatory issues by having the different parties face off in an adversarial manner through disputes between experts. That Facebook chose to tackle its fake news problem (in as much as this can be “tackled”) not by emphasizing the mechanical objectivity of its algorithms, but rather by drawing on the prestige of fact-checking institutions, is a hopeful first step.   Platforms are new; there is a great deal of interpretive flexibility in their underlying technical and institutional infrastructure. The future of media objectivity in an age of polarization, Trump, and social media platforms might lie in drawing on alternative civic epistemologies. That might be an area where we social scientists might make a useful contribution.

Contact Dr. Kelkar at: skelkar[at]berkeley.edu

By Dan Morrison, Vanderbilt University

Note: This is a revised version of the leading essay in the November 2016 issue of Skatology. Dan Morrison takes full responsibility for its content, and thanks Scott Frickel for his comments on an earlier draft.

Donald J. Trump is President-elect here in the United States. Articles like those Joe Waggle wrote in the November 2016 issue of SKATology on science policy under Republican, Democrat, Libertarian, and Green administrations both an artifact of pre-election history and an important document on what might have been. We do know that Mr. Trump garnered over 270 electoral votes and thus will be the next President.

As Waggle recognizes, we do not know much about what science policy under a Trump administration will look like except to the extent that any decisions will be made with an eye towards economic competitiveness and market dominance. We do know that Myron Bell, Mr. Trump’s choice to oversee the EPA transition from President Obama to Trump is a well-known denier of the overwhelming consensus on climate. His nominee for EPA administrator, Oklahoma Attorney General Scott Pruitt, has sued the agency he is nominated to run 14 times. One suit aimed to stop protections for his state’s air. Pruitt is known to deny scientific consensus on climate change and his selection has potentially devastating consequences for the recent Paris Climate Accord.

Based on our many discussions with colleagues in the immediate post-election period, I think it is likely that those who rely on federally funded research institutions such as the NSF, NIH, NEH, and others, are experiencing a profound level of anxiety. Those with “soft-money” jobs are concerned that their grants will be either cut, or that funding for their granting agency will be slashed to such an extent that future work is in peril. There are just too many unknowns at this point. Past Republican-controlled Congress sessions have voted to cut funding for political science. It seems likely that the incoming administration will finance its other priorities by reducing or eliminating several federally funded research programs, with the possible exception of research aimed at protecting national security or increasing economic competitiveness.

We may well be in an era of retrenchment. But we may also be in an era that is ready for sociological analyses of expertise and knowledge. Our area of the discipline may be more important than ever. We have studied the rise of new professions, the creation of academic disciplines, and the construction of expertise. Sociologists of science and knowledge have been active for decades in investigating how expertise is legitimated, and the links between legitimation and power. What might we do within the public sphere to advocate for justified beliefs without turning to naïve positivism?

Related to the problem of expertise is the problem of low-information, or active ignorance. In a 2008 article for Sociology Compass, Robert Evans wrote:

… how are we to understand decision-making in the absence of information? This problem is particularly acute for the political sphere where a disinterested or uninformed public can undermine the legitimacy of democratic institutionsbased on mass participation (228).

I have been reflecting on the earliest sociologists in America, the Atlanta and Chicago schools, seeking inspiration for what may be a difficult four years for those of us who would foster democratic values and want America to become America for all.

W.E.B. DuBois wrote in his The Souls of Black Folk, “Honest and earnest criticism from those whose interests are most nearly touched, –criticism of writers by readers, of government by those governed, of leaders by those led,–this is the soul of democracy and the safeguard of modern society” (1903: 45-46). I think that as scholars we have a great deal of responsibility moving ahead. If you are an American citizen, you may have special duties as well. We all must take up that responsibility and defend our society and our institutions, including our colleges and universities as sanctuaries for critical reflection and action. The philosopher and pragmatist John Dewey once wrote: 

Society exists through a process of transmission… this transmission occurs by means of communication of habits of doing, thinking, and feeling from the older to the younger. Without this communication of ideals, hopes, expectations, standards, opinions, from those members of society who are passing out of the group life to those who are coming into it, social life could not survive… Unless pains are taken to see that genuine and thorough transmission takes place, the most civilized group will relapse into barbarism and then into savagery (1916: 3).

As always, we have much to do, and several SKAT section members have written extensively about these issues. I am thinking specifically of scholars such as Alondra Nelson, Ruha Benjamin, and Tony Hatch.

Let us begin again in our sociological work that is also political and, if we take up the challenge, oriented towards justice.

References

Dewey, John. 1916. Democracy and Education. New York: Macmillan.

Evans, Robert. 2008. “The Sociology of Expertise: The Distribution of Social Fluency.” Sociology Compass 2: 281-298.

Note: This post has been updated to include information about Scott Pruitt, Mr. Trump’s nominee to lead the Environmental Protection Agency.