Are technologies political? Facebook and more

Are technologies political? While baking vegan chocolate chip cookies for a class last week, I wondered if my hand mixer—one of those amazingly durable 1970s machines passed down from my mother—might be imposing some sort of value judgment on me. OK, let’s not anthropomorphize my kitchen gadgets. But Ruth Schwartz Cowan, a feminist historian of technology, would argue that even household technologies have politics behind them, as well as profound social impacts. Consider this recent article in Wired: the design of the keyboard I’m typing on might have a minor impact on the words I unconsciously gravitate towards. Or consider the impact of Facebook on how teenage girls present themselves to the world. Today’s hyper-connected teenagers grow up in a world that is always “on,” and there are social consequences. Maybe I was just a teenage freak, but I when I was in junior high it was cool to wear pajamas to school...

In The Whale and the Reactor, Langdon Winner argues that we should more closely examine the politics behind technologies. He writes, "Over many decades technological optimists have been sustained by the belief that whatever happened to be created in the sphere of material/instrumental culture would certainly be compatible with freedom, democracy, and social justice" (Winner, p. 50). The kicker is, of course, that many of our technologies are not compatible with these ideals. The classic example in agriculture is how the University of California extension system introduced mechanical tomato harvesters. This not only changed the physical properties of tomatoes in the supermarket (bred to be durable, rather than tasty), but created an economic barrier that made smaller farmers go out of business. Other agricultural technologies, such as the fertilizer/seed/pesticide packages of the Green Revolution, and genetically modified foods, also favor larger farmers. This seems to not just be because larger farmers have more capital, stronger networks, and are thus earlier adopters of innovation, but there also something inherently autocratic in the technologies and throughout their development.

These themes are central tenants of Science and Technology Studies’ co-production idiom. Politics shape science and technology, and these in turn shape society. But society pushes back, too. From housewives who started using telephones for social calls rather than ‘business’ to farmers who use cell phones to monitor their crops and commodity prices, we have both formal and informal social means to regulate technologies. These would be considered the “social construction of technology” point of view, as opposed to the co-production or even technological determinism I hinted at earlier.

A really great thought experiment on the social construction of technology is the history of privacy. Despite the ever-shifting impacts of technology on electronic privacy and security, there may be a time in the future where no password is safe and every Cory Doctorow explores this in his short story, “Knights of the Rainbow Table” in the Tomorrow Project. When hackers can crack every password code, perhaps new social norms will catch up with technological advancement, in the same way that we don’t constantly rifle through our roommates, officemates, and neighbors’ belongings (unless you are living with a sociopath, in which case, I recommend you leave now!). 

Back to Facebook, I believe that many of these new norms are starting to form. While it may sound silly, teenagers swap online passwords with each other as a sign of trust and intimacy. Before the days of smartphones, I’ve shared passwords with my roommates in cases when I needed to call to check an email, submit an assignment, or banish myself from Facebook (i.e. letting your roommate change your password). I also trust that my Facebook friends won’t share my embarrassing photos beyond the network, but I’m also coming to terms that nothing I do on the internet will ever be completely private.

Although I have a certain faith in how social norms mediate our interactions with technologies, legal regulation is still important. I might trust my friends with silly photos from last Friday night, but I definitely don’t trust a stranger with my bank account.

Science and state power

"Harrowing a field with a diesel tractor, Seabrook Farm, Bridgeton, N.J." c. 1942, Library of Congress.

The connection between science and state power might seem tenuous to those who have not yet drank the Kool Aid. We know that science is used in political debates as the ultimate fact-checker. Is this new drug safe? Let’s do a risk assessment. What’s the trade-off of building this new dam? Let’s have an environmental impact assessment. But to anyone who’s studied the politics of environmental controversies, these scientific measures are hotly contested and imbued with political values.

James C. Scott’s fantastic book, Seeing Like a State, outlines how states have used scientific measurements and standardization to render social life and the environment visible, and thus, controllable. A city map can reflect necessary information like the location of businesses, and the layout of roads.  People are not trackable and taxable unless they have standardized and stable names, land tenure, locations, and ethnicities. But while these simplifications of social life are a necessary abstraction, they miss the nuances of societies, can have systematic flaws, and do not represent local resistance to top-down order (for example. Maps, censuses, and other technologies we use to make complex systems legible also shape how state power interacts with local autonomy. When wheat becomes a commodity to be measured, weighed, shipped, and sold, suddenly “agriculture” is not so much a social process as a means to an end. The mechanization of agriculture seen in the 20^th century reflects the expansion of commodity chains due to railroads and steampower in the 19^th century. See this post for an example of Scott's "high modernism" theory in China.

In Samer Alatout’s study of water politics in midcentury Israel, he shows how the social construction of water scarcity coincided with expansion of state power and centralization of water technologies. Instead of viewing science and politics as separate spheres, Alatout shows how “water scarcity and the strong centralized state were produced in the same technopolitical process" (p. 962). Focusing on estimates of water supplies in Israel, he writes that for the chief water engineer at the time, Aaron Wiener, “estimate reduction was a step in the right direction, towards a practical, empirical notion of the ‘scientification’ of water policymaking. He commented often on the fact that water policymaking during Blass's reign was anything but scientific” (p. 970).

Water estimates and their role in Israeli foreign policy are a good example of a “boundary object” that is used to negotiate between social and scientific spheres (although as I indicated earlier, the “boundary” itself is not so clear). And interestingly, people who seem the most capable of recognizing these boundary objects are STS scholars and conservatives. Throughout the article, I was thinking about a recent book I read, Merchants of Doubt by Naomi Oreskes and Erik Conway. In this book, the authors show how from the end of WWII and up to today, a group of scientists have used their influence to cast uncertainty on health and environmental reform. These doubt-mongering scientists, some of them hawkish Cold War heroes, believe that liberal environmental politics reek a bit too much of Communism. Smoking bans, acid rain regulations, and climate taxes all represent an expansion of state power over industry, and thus must be attacked in the only legitimate way: through science. They exploit the uncertainty of boundary objects like climate models.

Although Oreskes and Conway’s book is a rich piece of the history of science in politics, there is some unpacking left to do about the role of science and the state. Reading Scott and Alatout, there might be good reason for conservatives to worry about environmental politics being used as a tool to expand state power. Or in the case of climate change, non-state power as well (think “disaster capitalism”).

"Cherry orchards, farm lands and irrigation ditch at Emmett, Idaho," 1941, Library of Congress. 

Guess what, this is my 50th blog post! Many, many thanks to those of you who read, follow, and share my blog. According to Blogger, I've had over 5000 pageviews.

Works cited:

Samer Alatout, “'States of Scarcity': Water, Space, and Identity Politics in Israel, 1948-1959,” Environment and Planning D: Society and Space 26:959-982. 2008.

STS perspectives on the Green Revolution

Over the next few weeks, you'll be hearing a lot from me and some collaborators about the future of food and agriculture. Consider this a warm-up, although it's a bit academic. And if you're in the Phoenix area, check out this panel I'm participating in this week, "Feed 8 Billion."

The Green Revolution is an era of rapid agricultural innovation and diffusion that is critical to my own research, and I would argue, to the future of agricultural research. Narratives of the Green Revolution are invoked by different actors for different purposes; Robert Zeigler might invoke the Green Revolution as a reason to support public agricultural research. Activists like Vandana Shiva might invoke it to warn of the dangers of monocropped agriculture and top-down international development projects. I prefer to take the middle road, but the aim of my research is not to make a normative judgment about the Green Revolution. Instead, I aim to interpret how different visions of agricultural change and innovation drive organizations and technological development.

I have created a public folder of my essential Green Revolution articles, and I would also highly recommend these books by Kloppenburg, Perkins, and Cullather for an even richer perspective. There are so many things written about this topic, but I've attempted to cull it down to my favorites. I've also included my paper on the Green Revolution and the Population Bomb in Asia from 1960-1970, which I wrote for a class last year and hope to turn into a dissertation chapter. Please ask for permission if you'd like to cite or circulate my paper.

I'm going to highlight 3 papers for this post. They are articles I picked because they cover the basics of the Green Revolution, biotechnology, globalization, and some of the core STS concepts I want to explore in my research. The common theme between these 3 articles is agricultural innovation systems, and the dynamic between technologies and institutions/organizations.

Let’s start with Parayil’s 2003 paper on technological trajectories from the Green Revolution to the “Gene Revolution” (biotechnology and molecular techniques for plant breeding). Parayil borrows the concept of technological trajectories from a paper by Giovanni Dosi in 1982. The unique contribution of Dosi’s theory is that technological development occurs in a specific technological paradigm that both produces innovations, but also constrains these innovations to a specific trajectory. The physical properties of the technology and its path of development, the institutional environment that produce technologies, and the economic forces driving innovation all contribute to a specific technological trajectory. 

Parayil uses this theoretical framework to explain how the research organizations, technologies, and economic incentives during the Green Revolution are very different than today’s Gene Revolution. Other factors, like globalization, neoliberalism, and intellectual property rights also characterize today’s innovation environment. To Parayil, it is wrong and possibly dangerous to imagine the Gene Revolution as a continuation of the Green Revolution. I am proposing to empirically study an actual innovation system, using the case study of northwest India. What actors are involved in research, seed sales, and extension? To what extent are farmers included in participatory research, and does this feed back into the system? How do conceptions of biotechnology and the Green Revolution shape future imaginations of agricultural adaptation to climate change?

Onto the next article, Brooks (2011) on international agricultural research and global public goods (GPGs). Brooks discussed how the CGIAR (an international consortium of public agricultural research centers, several of which were critically involved in the Green Revolution) markets itself as a purveyor of GPGs and that the “CGIAR centres would now play a ‘brokering’ role in global, heterogeneous networks comprising a wide range of public and private institutions (Rijsberman 2002, 3). The implication was that ‘the CGIAR was uniquely placed to act as honest broker’ and steer these complex networks in directions consistent with a public goods research mandate (Brooks 2010, 4)” (Brooks, 2011, 70). Brooks frames her argument against a 2008 paper by Dana Dalrymple, an economist at the USDA who has promoted public international agricultural research since the Green Revolution. 

She uses the case studies of Golden Rice, iron biofortification, and the CGIAR’s HarvestPlus program to show how despite the CGIAR’s claims of knowledge brokering and new research paradigms, and despite ostensibly new research partnerships and institutional innovations, the CGIAR has maintained both institutional dominance (in a top-down paradigm) and technological and economic reductionism (assuming scale-neutral technologies, and silver bullet solutions to complex social problems). My research on climate change adaptation and agricultural research aims to uncover similar dynamics. How do international, national, and local agricultural research organizations (including public, private, and NGOs) use climate change as a leverage point for power? Have research paradigms actually changed because of climate change, or are the same technological and institutional goals maintained? 

Finally, Busch and Juska (1997) discuss political economy, actor network theory, and globalized food and agricultural systems. The authors frame their article against political economy approaches, which focus on social power. They claim that this approach generalizes and simplifies the range of actors involved, and demands that non-human actors (such as food and nature) are passive. Instead, they recommend embracing actor network theory, which seeks to remedy these oversights. They use the case study of Canadian rapeseed (canola) to show the relationships between scientific institutions (particularly plant breeding and organic chemistry), technologies, and nature that were necessary to make rapeseed oil edible for humans. Furthermore, the liberalization of global rapeseed markets led to shifts in production and consumption. I find the actor network theory approach to agricultural systems extremely helpful in empirically conceptualizing the connections between scientific research, commodity chains, and producers and consumers. In my own research, I plan on conducting a network analysis of rice and wheat research in northwest India. I’m not as interested in the global commodity chain, but rather the interaction between local, national, and international actors.

States of Knowledge: Autism, bird flu, and co-production

This week for class we read selected chapters from the book, States of Knowledge: The Co-Production of Science and Social Order, edited by Sheila Jasanoff. It's important to first understand the concept of "co-production" in the context of science and democracy. Jasanoff's co-production is the co-evolution, co-dependency, and obviously co-production of science and social order. This is a useful conceptual tool for studying science, technology, and society because it refuses to cede to technological or social determinism that is present in other social science scholarship. For example, the theories of Thomas Malthus are social determinist because they disregard the human capacity for innovation. More recently, the controversies around eugenics and intelligence testing (as I discussed last week) assume that intelligence is a "natural," or genetically determined, trait. A technologically determinist perspective would be how technology ultimately shapes our society. For example, one might argue that the confluence of highways, automobiles, and fast food restaurants are the cause of obesity in America. But this ignores the social determinants of obesity, and also the social transitions in post-WWII America that co-evolved with a car-centric, processed food-based society.

Jasanoff further separates co-production into two facets: constitutive and interactional. Constitutive co-production helps explain nationhood and legitimacy of knowledge; more simply, what we consider nature and society, and why. Interactional co-production is more concerned with how we know things. This is broadly referred to as "boundary work"- or interactions between science and society/politics. Looking to the Science section of the New York Times, I can easily find articles that resonate with each category. One article describes how "New Definition of Autism Will Exclude Many, Study Suggests." The American Psychiatric Association sets the standards of mental health diagnosis in the Diagnostic and Statistical Manual of Mental Disorders (DSM), with the newest revision causing fears of under diagnosis of autism or autism spectrum disorders. This really clearly demonstrates constitutive co-production, because the DSM definitions of disorders are shaped by both social norms and scientific knowledge. And there are implications for both science and society: presumably, the concern is that people who are not properly diagnosed will miss out on crucial health and social services. The scientific implications are also important: statistics will shift, doctors will change their practices of diagnosis, and new standards are institutionalized.

Another recent article helps demonstrate “interactional” co-production: “Scientists to Pause Research on Deadly Strain of Bird Flu.” As mentioned in the article, an absolute moratorium on research is seldom seen (even with stem cells, research could still continue under private funding). But it seems that cultural differences between America and Europe are playing a part. A Dutch virologist stated, “‘It is unfortunate that we need to take this step to help stop the controversy in the United States’… ‘I think if this were communicated better in the United States it might not have been needed to do this. In the Netherlands we have been very proactive in communicating to the press, politicians and public, and here we do not have such a heated debate.’” It’s funny how the same argument is used about agricultural biotechnology (genetic modification of foods); only switch the positions of the U.S. and Europe. And importantly, the article points out that although we have “never seen the scientific world so polarized, and that led him to urge the researchers to show good faith and flexibility by declaring the moratorium themselves.” This is a clear, although likely unintentional, reference to the idea that science governs itself, rooting back to Michael Polanyi’s “Republic of science,” and that science should be unfettered by government restrictions or impositions. In the realm of post-war science policy, old habits die hard.

Environmental science and politics: Book reviews

Having a bit of time off this week, I've read two books that both take a political ecology approach to environmental problems. Political ecology emerged from a certain tradition of social scientists, and really seeks to intertwine the social and natural aspects of the environment. Since both books are relevant to the themes of this blog and my own research, I thought I would do a quick review!

The first book was Critical Political Ecology by Tim Forsyth. I had the pleasure of meeting Dr. Forsyth over the summer, so I was really excited to read this book. Forsyth combines critical social theory with STS, philosophy of science, and his on-the-ground experience in international development work in South and Southeast Asia. The central theme of his book is that environmental science has been used to reinforce "environmental orthodoxies," which are similar to myths or narratives. Some of these key environmental orthodoxies are that population growth causes soil erosion, and deforestation causes loss of biodiversity. Forsyth shows that these arguments are used for specific political/normative agendas, but that alternative scientific approaches have actually revealed contrary data in some contexts. Each chapter reviews different case studies that touch on themes of democratic science, science-policy boundaries, global risk and uncertainty, and scientific expertise vs. indigenous knowledge. Overall, his book shows the tension between top-down environmental orthodoxies and local adaptations to the environment, and the limits of using scientific facts to make policy decisions.

The second book I read was Arun Agrawal's Environmentality (no connection to the photo above, but still funny). "Environmentality" is a form of Foucault's "governmentality," which roughly means rendering subjects governable. So environmentality is the making of environmental "subjects" through technologies of governance. The primary technology that Agrawal examines is the use of statistics in Indian forestry, starting in the mid-eighteenth century under British colonial rule. Agrawal takes both a historical and anthropological approach to the region of Kumaon, in northern India (looks like a horrible place for fieldwork). He uses historical sources as well as surveys and interviews to show how Kumaon villagers have a dialectical relationship with state-driven forest policy, which protects forests but limits local access. The villagers use some of the environmental rhetoric of protecting forests, while simultaneously using it to their advantage and resisting state control. This is a great analysis, because it confronts the shortcomings of a one-sided approach to development politics (i.e. either ignoring or too relient on indigenous knowledge and local adaptations).

The themes of local adaptations vs. global development/top-down power/technological interventions is seen throughout Forsyth and Agrawal's recent work, especially with regards to climate change, and is something I hope to explore in my own research on agriculture in India (once I figure out what I'm doing...).

Finally, I also recently enjoyed Paolo Bacigalupi's The Wind Up Girl, which is a science fiction novel about a dystopian, post-sea-level-rise, post-fossil-fuel world. Bacigalupi's dislike of agri-chemical companies is obvious, as they are the main antagonists in the hunt for the last remaining seed bank in Bangkok, Thailand. Intriguingly, the government in Thailand is dominated by the Environment Ministry, which usurped power because of the impacts of climate change and global pandemics. Perhaps my favorite aspect of the book is that in the absence of fossil fuels, energy is measured in calories since the only remaining energy sources are biological. This relates back to Agrawal's Environmentality-- making things into government subjects by classifying them-- whether it's carbon emissions or calorie intake.

[UPDATE] I also wanted to say THANK YOU to everyone who's reading and commenting! According to Blogger stats, I've had over 4000 pageviews this year. Not sure how accurate that is, but thanks even if you're not getting counted through GoogReadz or something. Happy New Year!

Conferences and sociotechnical systems

Flying is a constant, necessary (in)convenience in my life. While it’s great being only a 4-hour flight away from Michigan when I’m in Arizona, the endeavor requires careful planning, packing, arranging, and management of every little detail from my laptop’s battery life to remembering to drink water. I’m doing a lot of flying this month, and just got back from the joint conference of the History of Science Society, Society for the History of Technology, and the Society for Social Studies of Science. As a consequence of all this talk of science and technology, I can’t help but begin to see everything as “socio-technical system.”

If you’ve seen the movie “The Matrix,” you have an idea what graduate school is like for me. There’s a Facebook page for one of my advisors, Dan Sarewitz, that jokingly asks,

- Are you unable to sit through a traditional biology/chemistry/physics/engineering/economics course without constantly contemplating how your professor managed to "drink the kool-aid?"
- Do you constantly remind yourself that your science professors are but tiny cogs in a global innovation machine?
- Are you unable to look at a tomato without thinking about science, politics, labor economics, sociology, anthropology, Michael Crow, agriculture, geopolitics, innovation systems, the University of California, and climate change?
- Does the mere mention of the "linear model" make you shudder?
- Are you unable to synthesize your views on climate change in less than 5,000 words? 

If so, you are probably a former student of Dan Sarewitz. You will never hold a mainstream academic position, and your peers (and the public) will never quite be sure what your "deal" is. That's what you get for taking the red pill.

Yep, that sounds about right.

A major project of the science studies is to give social, historical, and political context to the technologies we use in our everyday lives. For example, I’m reading a book by Maria Kaika about urban water infrastructures. We don’t really think about where our water comes from every day. We turn on the tap and expect water to be there (in the Western, developed world, at least). What we don’t think about is what it takes for that water to get there and for an assured, constant, and instant supply of water at our faucets. During the rare times when the tap might go out, we get a profound sense of “uncanny” because our expectations are suddenly jolted as we realize water doesn’t just appear form the walls. The author writes about the hidden infrastructure of urban water. For example, let’s say you visit a dam someplace out west. We don’t really connect this with out water supply, and also the enormous amount of energy needed to move water from the source to tap. All of this is hidden from view and out of mind. Kaika argues that this is because of the artificial divide between “wild” nature and the sanitized urban home. So here we have not only a sociotechnical system, but a socio-technical-environmental system.

Back to airplanes, since I’m actually writing this on the plane! Airplanes, and the process of air transportation, are a more visible form of sociotechnical systems. We stare in awe at the massive planes used for transcontinental flights. But from the second you walk into the airport, you become immediately aware that you are part of a finely tuned system of both humans and technologies. We are enrolled, inspected, standardized, and shuffled into our seats. Usually everything goes well, but today after our flight landed, the electricity went out as we were leaving the plane. This was also an example of “uncanny,” even though it is a more visible system. We can see the nuts and bolts of the plane (and don’t get me started on rivets… we read a painstaking paper last semester about the technological innovation behind airplane rivets), but we still expect everything work.

Think about the complex and heavily embedded system behind energy extraction and production, and the technological disaster that this has caused. These aren’t just technological disasters though, they are most definitely sociotechnical disasters. It’s crucially important to realize that humans design, maintain, and run these systems (to the extent that we have control). But inevitably, tightly coupled systems, such as energy, increase the severity of human error and technological failures. The take home message is that we often don’t notice sociotechnical systems until they fail.

UPDATE: Here's a great link via Arijit on the nation's water infrastructure being ignored.

"How science works": A jaded pursuit of knowledge?

Image source.

As I get back into the swing of graduate school classes, I'll likely be blogging less frequently. But if you all keep sending me interesting articles, the more fodder I have for new posts!

A staple of STS theory, and other post-modern theories, is that "science" (defined roughly as an organized pursuit of/production of knowledge) is less objective than we'd hope. After all, scientists are human, and all human artefacts are shaped by our own experiences, biases, and institutional environments. So although not all STS scholars adhere to the full-blown post-modern relativism that there is no objective truth, I see the STS perspective as simply more critical of taken-for-granted assumptions about science.

There are plenty of examples from the History of Science about how science, at the time, was taken as the paragon of truth, only to later be totally de-bunked. The regime change from one scientific theory to another is what's known as  "paradigm shift." But perhaps science isn't just about finding out what's right and wrong in the universe. What matters is even what we decide to study. For example, STS scholar Scott Frickel writes about science and activism. In his 2004 book, Chemical Consequences: Environmental Mutagens, Scientist Activism, and the Rise of Genetic Toxicology, he describes how a group of scientists, influenced by the 1970s environmental movement, started a new, interdisciplinary field of "genetic toxicology." While building the scientific legitimacy of their field (which Frickel points out, is an act of advocacy itself), the scientists also strategically distanced themselves from the more "activist" arm of their academic society. I have a more detailed analysis on science and activism linked at the end of this previous post.

The recent controversy of science and activism centers around, of course, climate change scientists. The question is whether scientists can be pro-climate policy activists while still maintaining scientific integrity? However, the scientists themselves don't see themselves as activists. Here's a recent excerpt from an NPR article:

Science advances through a self-correcting system in which research results are shared and critically evaluated by peers and experiments are repeated when necessary. Disagreements about the interpretation of data, the methodology, and findings are part of daily scientific discourse. Scientists should not be subjected to fraud investigations or harassment simply for providing scientific results that are controversial. Most scientific disagreements are unrelated to any kind of fraud and are considered a legitimate and normal part of the scientific process.... (AAAS, 2011) 

Climate research works precisely in the same way. To politicize it, to persecute and scrutinize individual scientists as if they were corrupt politicians, is not only misguided but useless. Not all scientists are virtuous (and not all doctors, lawyers, bankers, or teachers either), but the whole point of the scientific process is to free itself from such personal flaws: sooner or later, fraudulent or wrong data is uncovered and the path toward certitude is restored. Errors may persist for a while, but not for a very long while.

The author is speaking of traditional paradigm shifts, and the self-correcting view of science described by Michael Polanyi. The problem is that this view of science ignores what we know about scientists: they too, are human. A "free market" pursuit of science is not necessarily best for society as a whole. This might be partly because scientists have long been a homogenous social group, although this is changing.

A round-up of recent news articles adds some interesting perspectives to the mix:

"Biased by Brilliant" (bonus points for referencing philosopher of science Heather Douglas)

Doesn’t the ideal of scientific reasoning call for pure, dispassionate curiosity? Doesn’t it positively shun the ego-driven desire to prevail over our critics and the prejudicial urge to support our social values (like opposition to the death penalty)?

Perhaps not. Some academics have recently suggested that a scientist’s pigheadedness and social prejudices can peacefully coexist with — and may even facilitate — the pursuit of scientific knowledge.

"It’s Science, but Not Necessarily Right"

Scientists can certainly point with pride to many self-corrections, but science is not like an iPhone; it does not instantly auto-correct. As a series of controversies over the past few months have demonstrated, science fixes its mistakes more slowly, more fitfully and with more difficulty than Sagan’s words would suggest. Science runs forward better than it does backward.

"The objectivity thing (or, why science is a team sport)."

In both the ideal of reproducibility and the practice of peer review, we can see that the scientist’s commitment to producing knowledge that is as objective as possible is closely tied to an awareness that we can be wrong and a desire not to be deceived — even by ourselves.

Science is a team sport because we need other people in order to build something approaching objective knowledge.

However, teamwork is hard.

"Toni Scarpa: Reviewing peer review"

The goal was to ask people to focus more on impact and significance. Peer review is simple — I think it should ask only two questions. First: Is it worth doing? That is impact and significance. If the answer is yes, then you ask the second question: Can they do it? In the past we were asking those questions in reverse.

So I'm not sure if I'm ready to come to any conclusions about what this means for climate science, but it certainly highlights science as a human pursuit, subject to the same biases and ethical dilemmas as any other.

Seeds and sociotechnical imaginaries

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One of the coolest things about Science & Technology Studies is that it blurs the line between the social sciences and humanities. Scholars from the disciplines of anthropology, history, sociology, women's studies, and political science (among others) all collaborate to understand the world from this unique lens. The benefit I enjoy from this perspective is that I can take a more creative, literary approach to some of my research. For example, just today I was thinking about this post, and something about these pictures reminded me of none other than the Jack and the Beanstalk fairy tale! Stick with me, and I'll actually try to make a convincing argument for the connection to climate change.

Image source.

Image source.

I've been thinking about how we use the "imagination" of plant DNA, genetics, breeding, biotechnology, as a future technology to help crops adapt to climate change. For example, if you take the DNA from a warmer climate plant and breed it (either through conventional crossing, or biotechnology/recombinant DNA methods) with another plant with desired characteristics, farmers can then grow that plant without having to radically change their methods or machinery. I am developing a fair amount of criticism of this imagination because of two main things:

1) Agricultural technologies and practices have radically changed over the past 50 years, and will continue to do so (thus projecting a predicable, stable yield output is somewhat futile).
2) We cannot ignore the social and economic context of global agriculture and the scope of challenges that farmers face every day (reducing the complexity of climate change adaptation).

There are also questions of what are we adapting, what are we sustaining, and who will benefit/lose out? Many people attempt to address the first two questions with science; however, they are fundamentally based on human values.

STS provides some useful tools for dealing with scientific imaginations of the future: Sheila Jasanoff calls these "sociotechnical imaginaries," which, similar to the co-production of science and society, are visions of the future that embed and prescribe certain social assumptions. Jasanoff and Kim (2009) use the example of how the United States and North Korea had very different visions of how nuclear power should be used. One technology, but two different interpretations. This goes to show another theme of STS, which is how within "sociotechnical systems," you cannot always separate technologies from their social context. The two are deeply intertwined. This also means that there are no socially-neutral technologies- they will always benefit some, harm some, and have unforeseen consequences.

So imaginaries tend to reduce the complexity of global issues, and also obscure the social implications with scientific certainties. This is very problematic, and I wonder how the continued imagination of plant genetics as a savior will hold up under climate change. Until next time, read this.

Experts, Expertise, and Impure Science

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Yesterday we finished our discussion of The Honest Broker by asking ourselves some very provocative questions about the future of science policy advice. We asked questions like, "why is science privileged as a tool in decision-making, and scientists privileged as experts on matters that are often about values?" Involving scientists in policy-making about issues as diverse as breast cancer research to environmental controversies often results in one outcome: "we need more science!" Yet I made the point that we are often operating outside the bounds of "normal science"- this is something that STS scholars have called "post-normal science." The late Stephen Schneider has an excellent explanation of post-normal science with regards to climate policy. Post-normal science is the antithesis of "normal," but it is also the opposite of the ideal of "pure science." And pure science, of course, is often even regarded by scientists to be unachievable in practice. Pure science plays straight into the linear model of science.

So is "impure science" the same as "post-normal science"? We're about to find out. If I had one book to recommend from all of the reading I did last year, it would be Steve Epstein's Impure Science (Amazon, Google books). Epstein’s book is all about how the boundaries between expert and activist become blurred as each shape the other. It's about how a group of AIDS activists worked to challenge the biomedical model of drug testing that required slow, precise double-blind experiments, in order to more rapidly treat AIDS patients with experimental drugs under the "community-based" research model.

The chapters I've read gave brief history of AIDS clinical trials and the associated ethical issues; the emergence of community-based research and the breakdown of expertise and power in medicine; and the landscape of AIDS activism and how activists framed AIDS and their own expertise of the science of AIDS drugs (see also this related article by Epstein). Epstein’s argument is that AIDS activism both produced legitimate results (from community-based research) as well as challenged the structure of FDA regulation, and thus challenged the norms of “pure science.” This, I think, is the perfect example of post-normal science, and what STS scholars call "extended peer communities"- opening the research and decision-making process to non-scientists, including activists, patients, and community health practitioners. The figure above is supposed to show how in cases of post-normal science, the group of experts must be expanded beyond just scientists. I believe that this model could be applied to other issues of health and environmental issues that have high uncertainty and values that need to be reconciled.

If you'd like to read more about experts and activism in environmental controversies, I wrote a paper about it last semester. It's more or less a literature review of STS things, but hopefully you can find some nuggets of sapience.

5) Science communication and climate change

Image Source.

A topic that frequently comes up between me and my colleagues at Michigan State University this summer is of science communication. At the Science and Democracy Network meeting that I attended last week, one of the most contentious topics was over climate change science and communication, and what is our role as scholars to clarify (or "complexify," as is usually the case) the discourse.

So I thought I'd put together a resource list of blogs and papers on the subject of science communication, from an STS perspective (and particularly about climate change). First, Alice Rose Bell has a great blog on science communication, and even already has a helpful resource list! My other favorite climate change communication blogs are Dot Earth by Andy Revkin, Age of Engagement by Matthew Nisbet, Open the Echo Chamber by Edward Carr, and The Intersection by Chris Mooney. While I don't always agree with the partisan positions of many of these bloggers, I find myself enraptured by their interesting reflections on the latest research and controversies in climate change science and communication.

One of the contributions of STS research to science communication studies is of reshaping the "deficit model" of science communication into more nuanced views of public understanding of and participation in science. The deficit model is similar to both the "loading dock" and "linear model" of science and policy, in that it upholds scientists as disconnected experts, and that the public is an "empty vessel" to fill with objective knowledge. Some great papers on new models of science communication are "Do Scientists Understand the Public?" by Mooney (2010) and "What's next for science communication?" by Nisbet and Scheufele (2010).

So why did I open this post with a political picture? Because there is solid evidence that despite levels of scientific knowledge, political affiliation is the biggest determinant of whether U.S. citizens believe in climate change (summary here, full article by McCright and Dunlap (2011) here). I was lucky to take a class with Aaron McCright during my undergrad at MSU, and this really sparked my interest in the science politics of climate change. Since I took that class two years ago, I've been following the climate change communication literature. To start off, a classic article you need to read is "Making climate hot" by Susanne Moser and Lisa Dilling (2004). Communicating climate change is inherently difficult because of the high-level science as well as framing of risks and uncertainties, but Pidgeon and Fischhoff (2011) have some advice on framing climate uncertainty here.

And if you're interested in the whole "climate skeptics" debate, you need to read Naomi Oreskes and Eric Conway's book, Merchants of Doubt. Also, my new favorite blog resource is "Skeptical Science," which does a really good job at clearly communicating the science behind climate change, and addressing skeptical claims. Finally, Chris Mooney once again comes through with some commentary and a list of resources. Interestingly, even in the case of climate skeptics, the deficit model proves false. More scientific knowledge does not automatically make people "believe" in climate change. People's political orientations have a strong impact on what information we will use to support our own values. And overwhelmingly, even in the face of "Climategate" and uncertainty, the majority of Americans trust scientists and believe in climate change and support energy policy.

I want to conclude by saying that none of this is simple. Sometimes when I'm telling people about my research, I avoid the topic of climate change because I don't want to get into a debate. But while working at MSU this summer and last, we've noticed that when you sit with people face to face, and don't impose your own views but rather ask about their own thoughts and experiences, it leads to a more productive conversation. And having worked in a lab during my undergrad, I know how hard it is to "get out there" and communicate science- but there are a few easy ways, from working with student groups of all ages, to writing an effective op-ed, to learning how to present your research in a way that's accessible to non-scientists. An insightful comment on Alice Rose Bell's blog states, "if you want to reach young audiences, stop thinking of them as audiences and don’t merely involve them: work out what’s central about your project and invite them to do that."

2) Science-practice and science-policy boundaries

Image source: Alice Rose Bell, 2010.

My first few posts have been focused on science for decision-making and innovation. This next section will highlight the role of mediators between the spheres of science and policy, or what STS scholars refer to as “boundary organizations.” Like my first post, this will be a brief review of the literature, and in later posts I’ll look at specific examples of boundary organizations at work.

The concept of “boundary organizations” is extremely relevant to- you guessed it- agriculture extension work! The traditional model of extension, of course, is the top-down, “loading dock,” basic-to-applied research model. But complex problems like climate change pose new challenges for scientists, farmers, and extension educators. This is why some scholars are working to reshape this model. Extension is a mediator between science, policy, and stakeholders. It is not simply a provider of information, but rather a decision support system. Incorporating feedback from farmers and other stakeholders is important to the mission of university extension programs, and critical for addressing global challenges of the 21st century.

David H. Guston, William Clark, Terry Keating, David Cash, Susanne Moser, Clark Miller, Charles Powers. (2000). “Report of the Workshop on Boundary Organizations in Environmental Policy and Science.” Global Environmental Assessment Project. http://www.hks.harvard.edu/gea/pubs/huru1.pdf

• In 2001, the journal Science, Technology, & Human Values ran a special issue on so-called “boundary organizations” (see end of this blog for full references). Dave Guston is renowned scholar of political science and science policy theory. His idea of boundary organizations is that the realms of science and policy are not entirely separate; there are actors who span and negotiate between the two. This report contains a summary of all of the articles published in that journal. Many of the examples of “boundary spanners” deal with issues related to agriculture and climate change. David Cash shows extension’s role in negotiating water use in the U.S. High Plains states. He discusses the history of extension and multiple scales of the science/policy interface in this case. Clark Miller studies the politics of climate science. In this paper he argues that the international “climate regime” doesn’t fit neatly into the boundary organization model, and instead he proposes the term “hybrid management” for the function of organizations like the IPCC.

Cash, D.W. et al. (2003). “Knowledge systems for sustainable development.” Proceedings of the National Academy of Sciences. http://www.pnas.org/content/100/14/8086.full.pdf+html

• This article ties together some of the theoretical concepts on boundary organizations presented by Guston and others with a set of case studies of global environmental development. The authors represent both STS and “sustainability science” scholars, led by W.C. Clark. It also discusses science policy communication, in which they identify salience, legitimacy, and credibility as the main themes in providing useful information.

Cash, D.W., Borck, J.C., & Pratt, A.G. (2006). “Countering the Loading-Dock Approach to Linking Science and Decision Making.” Science, Technology, & Human Values, 31, p. 465-494. http://sciencepolicy.colorado.edu/students/envs_5100/Cashetal2006.pdf

• David Cash has another great example of boundary organizations and how they work. He proposes four mechanisms for them to work: convening (bringing people together), translation (communicating between different audiences, for example, science and the public), collaboration (working on a project with multiple interests represented), and mediation (finding mutual ground in conflicts). The “loading-dock approach” is a poor model of communication: it involves just getting the data out there, but not doing any follow up or getting any feedback. Cash et al. use the case study of communicating climate forecasts to show how participation from stakeholders is crucial to the 2-way communication between science and decision-makers. This is sometimes referred to as the “co-production” of knowledge (although other STS scholars use to work co-production in a different way, meaning the co-evolution of scientific knowledge and social systems/order).

Breuer, Norman, Clyde Fraisse, and Peter Hildebrand (2009). “Molding the pipeline into loop.” Journal of Service Climatology.

http://www.journalofserviceclimatology.org/articles/2009/Breuer-2009-JSC.pdf

• Our friends down south are blazing the path for extension’s role in helping farmers adapt to the impacts of climate change. This particular article describes how they used participatory dialogue with farmers and extension educators to create a website to provide information about regional crop outlooks based on climate forecasts. They call this a decision support system. For more information, see their 2010 report here. And for more comments on why agricultural extension needs to move beyond the linear model, read John Gerber's 1994 article here.

[Full articles from the STHV 2001 issue that have free access:]

Guston, David (2001). “Boundary Organizations in Environmental Policy and Science: An Introduction.” Science, Technology, & Human Values 26. http://www.cspo.org/_old_ourlibrary/documents/boundaryorgs.pdf

Cash, David W. (2001). “‘In Order to Aid in Diffusing Useful and Practical Information’: Agricultural Extension and Boundary Organizations.” Science, Technology, & Human Values 26. http://belfercenter.ksg.harvard.edu/files/In%20order%20to%20aid%20in%20diffusing%20useful%20and%20practical%20information%202000-10.pdf

Miller, Clark (2001). “Hybrid Management: Boundary Organizations, Science Policy, and Environmental Governance in the Climate Regime.” Science, Technology, & Human Values 26. http://www.cspo.org/_old_ourlibrary/documents/hybrid_management.pdf

I hope this blog post on boundary organizations was useful to you! If you have any questions, recommendations, or if something from the articles is not clear, please leave me a comment!

The linear model: science to policy

Image source: FY 2012 NIH Budget Roll-out, PowerPoint Presentation, February 15, 2011.

In my last post, I brought up the "linear model" of basic to applied research. This is pervasive at the highest levels of U.S. federal science agencies: for example, the image above is from a presentation by Francis Collins, the director of the National Institutes of Health (NIH). The NIH has recently been under attack for not producing breakthroughs in biomedicine that can be applied to society. Looking at the statistics, the United States spends the most on health care (per GDP and per capita) than any other developed country, yet we rank 24/30 for life expectancy of these developed countries (source: Crow, 2011). And we spent 26.6 billion on NIH-funded scientific research in 2010. There's not simply a "gap" in the pipeline that links science with society; there's a fundamental mismatch of research funding and goals, and with health outcomes. Many of the health-related outcomes we strive for do not require more basic research, but rather changes in social, behavioral, and economic factors (access to cheap, nutritious food, preventative medicine, cessation of smoking, etc.).

Another version of the linear model as a research "pipeline."

A recent report by a medical advocacy group promotes the linear model that investment in the NIH has led to positive economic outcomes, such as creating public and private jobs. That's great, but that still doesn't answer the question about health outcomes. For example, what's the difference between creating medical jobs, and simply endowing the arts and creating more jobs for artists? A good answer is that we use science for more than just finding cures; we also use it for guiding policy decisions and making politics more transparent through a common language of science.

STS scholars like Yaron Ezrahi have written extensively on how science is necessary to democratic politics because we can require politicians to justify their actions. "Seeing is believing" has been a mantra of science since the 1600s, and science can be used to "see" things like environmental and health impacts. But most of the time, science is not so easy to translate into politics. The case of climate change, and other environmental debates, are a good example of this.

This brings me to the second type of the mythical "linear model": the science-to-policy model. Roger Pielke, Jr. writes about this in The Honest Broker, which I will once again recommend. Like the NIH, the Intergovernmental Panel on Climate Change (IPCC) is part of a scientific authority that believes that more science=good policy outcomes. For quite a few years now, the assumption has been that science tells us climate change is bad, therefore we need policy to stop carbon emissions. In this model, the scientific experts appear to be removed from the politics (the "Mertonian ideal") However, climate change is more complicated than just carbon emissions, and this linear model limits how we can deal with the impacts of climate change that we cannot stop. Dr. Silke Beck is a German social scientist who writes about this in an article called, "Moving beyond the linear model of expertise? IPCC and the test of adaptation," published in the scientific journal Regional Environmental Change in 2010.

According to the linear model, humans cause carbon emissions, carbon emissions cause climate change, and climate change has impacts that we must adapt to. If we are unsure of any of these steps, policy-making becomes a gridlocked debate over the science (which is full of inherent uncertainties, even when nearly all scientists agree that climate change is happening because of humans). Beck's analysis explains why more science has not led to better policies. In the linear model, solutions to climate change are restricted to limiting emissions. But there are other options: policies to promote overall adaptive capacity, and win-win improvements to infrastructure and technological innovation.

Beck's alternatives to the linear science policy model include promoting useful science that will aid decision-makers in addressing climate change impacts. She also calls for bottom-up involvement of local stakeholders (like farmers). This analysis relates not only to my previous post on "science for decision-making," but also future posts where I will discuss public participation in science. As a final thought, Dan Sarewitz and Roger Pielke wrote a great article in 2007 about reconciling the "supply" of science with the "demand" of social outcomes. They write,

"The resulting picture is complex and yields no single, straightforward model for how knowledge and application interact; yet one feature that invariably characterizes successful innovation is ongoing communication between the producers and users of knowledge." (Sarewitz & Pielke, 2007, p. 7)

Sources:

Beck, Silke (2010). "Moving beyond the linear model of expertise? IPCC and the test of adaptation." Regional Environmental Change. DOI 10.1007/s10113-010-0136-2

Crow, Michael (31 March 2011). "Time to rethink the NIH." Nature 471, 569-571.

Sarewitz, D. & Pielke, R. Jr. (2007). The neglected heart of science policy: reconciling supply of and demand for science. Environmental Science and Policy, 10, 5-16.

1) A new science for decision-making

"Science" means many different things to many people. Science is an action, a set of methods for hypothesis testing; science is a result, a way of illuminating the world around us. By "science," I mean the combination of the practice and use of organized, institutional science. We typically think of science as something that happens in the laboratory. Maybe a spark of discovery leads to a new cancer-fighting drug. But we now know that science happens all around us. Citizens can collect air samples from their neighborhood and test the level of toxins. "Basic" research discoveries don't always lead to cures for devastating diseases. That's why I'm calling this post "A new science for decision-making."

This summer I'm working with Michigan State University Extension on a project about climate change and agriculture. Our guiding idea is of communicating climate change science and policy as not just a top-down, one-way street, but as a participatory process for scientists, policymakers, and stakeholders (farmers and anyone involved and affected by climate change). During my first year of graduate school at Arizona State University, I discovered that other people actually write about this! Thus, I am collecting resources that I hope you will find interesting and helpful. I have started from the perspective of Science and Technology Studies (STS, also related to the broader “social studies of science”). STS tends to take a critical look at the scientific processes of research and development and science and technology policy. The intended audience of my resource is interdisciplinary academics and science policy practitioners who are interested in the broader theoretical and practical relevance of their work. Special note: the articles are not in order of author, but rather the order in which I think they should be read for each set. Also, I've included a glossary of words that are critical concepts but may be unfamiliar to most people. Work in progress, May 2011. Comments appreciated!

Pielke, Roger, Jr. (2007). The Honest Broker: Making Sense of Science in Policy and Politics. Cambridge: Cambridge University Press. Available at Amazon.com

• This short book is an excellent guide to some of the principles of science policy, and particularly the role of scientists in political debates. If you’re looking to get started in learning about science policy and why things like the climate change debate have gotten so complex and confusing, this is the place to start. Also check out Roger's blog!

Kunseler, Eva (2007). “Towards a new paradigm of science in scientific policy advising.” http://www.nusap.net/downloads/KunselerEssay2007.pdf

• This short essay gives a good overview of the distinction between “normal” and “post-normal” science. Kunseler uses the framework of a “paradigm shift” which is the change from one set of widely accepted views about science to another. As referenced, Funtowicz and Ravetz (1993) are best known for introducing “post-normal” science, where they provide a framework for a new type of science needed for today’s uncertain and complex environmental problems. Like Jasanoff (next article), they call for more dialogue with non-scientific stakeholder communities.

Jasanoff, Sheila (2003). “Technologies of Humility: Citizen Participation in Governing Science.” Miverva 41. http://sciencepolicy.colorado.edu/students/envs_5100/jasanoff2003.pdf

• This article is a great starting point for some of the main issues that confront contemporary science policy and public participation in these political decisions. Jasanoff is a leading STS scholar and often focuses how science is used in federal regulatory decisions. Her proposed “technologies of humility” turn traditional scientific norms on their head.

Sarewitz, Daniel (2000). “Science and Environmental Policy: An Excess of Objectivity.” http://www.cspo.org/products/articles/excess.objectivity.html

• Sarewitz is another well-known science policy scholar. This book chapter is an insightful commentary on how science can actually impede the political process. Political debates focus on disputable and uncertain facts while ignoring underlying value conflicts in highly politicized environmental issues. The “excess of objectivity” refers to the incompatibility of multiple fields of science, and how while each field claims objectivity, they drive controversy and muddy the political waters.
• See also “How science makes environmental controversies worse.” By Daniel Sarewitz, 2004. http://www.cspo.org/_old_ourlibrary/documents/environ_controv.pdf

McNie, Elizabeth. (2007). “Reconciling the supply of scientific information with user demands: An analysis of the problem and review of the literature.” Environmental Science & Policy 10. http://sciencepolicy.colorado.edu/admin/publication_files/resource-2486-2007.03.pdf

• This final paper is a great tie-in between this section and the next (coming soon!). McNie takes a case-based, fairly non-theoretical approach to the “problem of linking science to decision-making” (p. 18). She outlines models of public participation in shaping science for decision-making.

Vocab:

Extended peer community/review: the proposal that scientific practice should be reviewed by not just scientists, but stakeholders. For example, breast cancer patients and activists would be involved in selecting what research projects to fund.

Linear model: the idea that “basic research” leads to fundamental breakthroughs that can be applied for economic growth. Basic research=lab/bench research, supposedly removed from society. Applied research=scientific discoveries applied to societal problems or for technology. Many science policy scholars now question this model, since many “discoveries” come from non-science, and science and technology are involved in a complex and iterative relationship. See Donald Stokes' Pastuer's Quadrant.

Mertonian ideal: science characterized by “universalism, communism, disinterestedness, and organized skepticism (Merton, 1973)” (McNie, 2007, p. 23)

Post-normal/"Mode 2" science: the evolution of scientific practice (or knowledge production) in a world of highly complex, uncertain, and interdisciplinary problems.

Social contract of science: the implicit agreement between scientists and the government/public that science should be funded based on peer review/merit, and without intervention. Based upon the “linear model” promoted by Vannevar Bush.

Well-ordered science: a proposal for aligning scientific research goals with societal goals. Based on Philip Kitcher’s argument in Science, Truth, and Democracy.