Earlier this month, I wrote about potential risks of sharing preliminary findings from the field, especially when they are related to a major social media company like Facebook. As anthropologist Daniel Miller discovered, doing anthropology in public carries the danger that journalists, bloggers, and others will pluck an ethnographic morsel from its context, and circulate it unmoored from those origins. Some news commentators, for example, reacted with panic to his contention that Facebook is “dead and buried” for some teen users in the UK. But if we don’t reach out to share our work, we equally risk provoking those who castigate academics for being too insular and our research too inaccessible. The debate about scholarly engagement in public resurfaced with renewed vigor last week (Just Publics @ 365 has a nice roundup) in response to New York Times’ columnist Nicholas Kristof’s piece “Professors, We Need You!” (Feb. 15, 2014).
I won’t spend much time rehashing the debate (as it were)—most of you are probably familiar by now with Kristof’s tired assertion that academics (“professors”) only write for specialized niche audiences and don’t pursue topics directly relevant to public life. But Kristof’s piece set off a wave of responses from academics who resolutely see themselves as engaged with non-academic audiences, and coalesced on Twitter around the hashtag #engagedacademics. In contrast to Kristof’s poorly informed views, a profusion of academic blogs, Twitter feeds, and news columns aim to relate scholarly work and insights to current topics of public interest—including this blog! So why didn’t Kristof realize this, and what should we do about—that is, we as academics, but also we as the public (or publics)?
Kristof was primarily targeting the quantitative social sciences, especially political science—as Kerim at Savage Minds points out, anthropology rarely appears in these debates over the relevance of the social sciences:
The thing is, anthropology is full of public intellectuals. You see anthropologists across all different forms of media, from leading newspapers to blogs, to local talk radio. You see anthropologists working on behalf of communities all around the world as well as working as bridges between communities. And you see anthropologists working daily with the large portion of the public that is in school, training the next generation of public intellectuals.
So, if that’s true, why does the discipline always seem to be in a crisis about the state of our public intellectuals? Why do we feel so marginal to public discourse? Why do we barely even get mentioned in debates like the one that erupted in response to a certain op-ed columnist?
Kerim offers three excellent suggestions for why we often feel marginal to these discussions despite a lively, ongoing tradition of public engagement in anthropology. First, anthropological methods ground us in the specificities of what we research, so we are more likely to be engaged in conversations about our particular topics and avoid generalizing. Two, we are often oriented towards publics very different from those many in the news media imagine. Three, anthropological (and other critical) perspectives call into question the entire capitalist enterprise that shapes dominant public discourse, making it difficult even to get the conversation on the same page. So what do we as anthropologists and STS scholars think about how to write for diverse audiences and how to make our research findings accessible? For example, how could public writing better fit into academic career trajectories, such as for tenure files? And what would more partnerships look like between qualitative social scientists and journalistic or policy endeavors?
Finally, as a footnote to this discussion, the New York Times published an editorial a day after the Kristof piece on the harm caused by adjunctification in higher education. I find it ironic, though not shocking, that the Times presents these contradictory viewpoints without much self-awareness, taking professors to task for insufficient public engagement with one hand, while acknowledging changes in the university that are making academic life increasingly precarious for the majority of professors with the other. Clearly these tensions need to be resolved before we can have a meaningful conversation about how social scientists should be engaged in public discourse.
Over the last two years I have been conducting research into amateur biology in and around Silicon Valley. During that time, I have worked as a volunteer in a DIYBio lab and on a pair of laboratory projects, one an unlikely precursor to the Glowing Plant project and another which fell into the dust bin of scientific history. Which is to say, for every project that captures media attention and attracts funding like Glowing Plant, there is an equally interesting project struggling to generate interest and find collaborators. With that in mind, I want to discuss some of the tensions within DIYbio laid bare by success of the Glowing Plant Kickstarter campaign.
Glowing Plant needs little introduction, as it has been the subject of sustained media attention since the Kickstarter campaign it launched early this summer. To give a brief technical overview, Glowing Plant intends to take a luciferin system from the marine bacteria Vibrio Fischeri, which is found in squid, and place it into an Arabidopsis plant, thus causing the plant to bioluminesce at night. As outlined on their Kickstarter page, to effect this transformation they plan to use the software program Gene Compiler to design DNA sequences then have these sequences laser printed by Cambrian Genomics. Once printed, the DNA will be sent to the Glowing Plant laboratory via Fed-Ex (the standard way to move DNA around the world) and then transformed into the Arabidopsis plant via agrobacterium. This portion of the project is regulated by material transfer agreements governing the movement of recombinant DNA between laboratories and, due to the use of agrobacterium, no plants transformed in this manner can leave the Glowing Plant laboratory. However, once the plants transformed with agrobacterium are deemed to glow enough, a final transformation will be done with a gene gun. It is the use of the gene gun that allows Glowing Plant to ship a genetically modified organism (GMO) to consumers without regulatory oversight. Here Glowing Plants follows a strategy pioneered by Monsanto to market GM bluegrass.
To date, most commentary around the Glowing Plant project has concerned the ethics of biotechnology in general and the specific ethical implications of using biotechnology to make a consumer product in particular. But as the Monsanto case illustrates, this is not a strategy unique to Glowing Plant. Though, Glowing Plant is an easier legal target as they lack Monsanto’s war chest. But, I would like to emphasize a different aspect of the project: the role of hype in the crowdfunding campaign and the claims made by the organizers for the ease and effectiveness of this technology. Keep in mind that while much of the critical commentary on both pro and con has assumed this plant can be created (it is a greater technical challenge than making bluegrass), the plant is still hypothetical and its creation is not a certainty. Apart from the still hypothetical existence of the plant, there is speculation, due to the energetic requirements of light production, over whether the transformation can produce a light visible to the naked eye.
As I hinted at above, despite starting out in DIYBio lab, the Glowing Plant kickstarter campaign was sponsored and supported by a number of startup companies associated with Singularity University, and it maintains close ties to its startup ecosystem. The core team comprising the Glowing Plant project consists of one Stanford trained PhD conducting laboratory work, one Stanford post-doc, and a former Bain & Company consultant. Further, prior to receiving funding Glowing Plant hired a digital marketing firm to manage its Kickstarter and PR campaign. Though often portrayed as the product of the wisdom of the crowd, the pump was primed well before the Kickstarter campaign was underway. In this sense, Glowing Plant follows the classic Silicon Valley pattern of the well-supported disruptive startup pioneering a new market, consumer synthetic biology in this case, by forcing a product through a regulatory grey area.
Unsurprisingly, Glowing Plant has been the subject of much angst within DIYBio, both over the manner of the project’s exit from the DIYBio laboratory where the idea was hatched and the preliminary lab work conducted, and over the project’s aggressive approach to regulation. Most DIYBio laboratories ask for no monetary commitment beyond individual membership dues or class fees and struggle financially as membership often ebbs and flows. In this environment, the departure of a popular and compelling project from a lab creates a difficult gap to fill. Glowing Plant’s approach to regulation and blanket claims of environmental safety also threaten to bring regulatory scrutiny to DIYBio as a whole, which to date has been a modest and self-regulating field. Already, Kickstarter has issued a category ban on GMOs, and Glowing Plant has moved from working at a public DIYBio laboratory into a private laboratory at an undisclosed location.
All of which raises the question posed by the title: What is the relation between Glowing Plant’s ambitions and DIYBio’s oft-stated goals and code of ethics? The rhetorical appeal made in Glowing Plant’s Kickstarter video is not to the ideals or ethics of DIYBio, but rather to the frontier, which indexes an entirely different and distinctly American set of ideals. As co-founder Anthony Evans says in the Glowing Plant kickstarter video, “our generation’s frontier is synthetic biology, our guide nature itself.” Where the DIYBio code of ethics draws on commonalities across distal polities of amateur biologists to urge self-regulation, moderation, and action in the common interest of amateur inquiry, Evans’ appeal to the frontier connotes an unregulated individualism coupled to the exploitation of a peculiarly American approach to regulation, in which an action not explicitly illegal is implicitly allowed.
Anonymous is a banner used by individuals and as well as multiple, unconnected groups unfurling operations across the globe from Brazil to the Philippines, from the Dominican Republic to India. Since 2008, activists have used the name to organize diverse forms of collective action, ranging from street protests to web site defacement. Their iconography—Guy Fawkes masks and headless suited men—symbolically asserts the idea of anonymity, which they embody in deed and words. To study and grasp a phenomenon that proudly announces itself “Anonymous” might strike one as a futile and absurd exercise or exercise in futility and absurdity. A task condemned to failure.
Over the last five years, I felt the sting of disorienting madness as I descended deep down the multiple rabbit holes they dug. Unable to distinguish truth from lies, and unable to keep up with the explosive number of political operations underway at one time, a grinding doubt settled deep into my mind many times. There was no way I could get the story right, get at all the nuances, much less all the cabals that populate Anonymous, I often told myself. Gaining access and the trust of scores of individuals who tunnel and mine and undermine, who desire to be incomprehensible, concealed and enigmatic to slightly rephrase Nietzsche’s opening to DayBreak, often felt like an impossible task.
They have been devilishly hard to study but not impossible. Time has been a kind friend. Sticking around over a five year period has certainly helped, especially as I met more participants in person. I protested with Anonymous on the streets in New York City and Dublin and attended court hearings as hackers received sometimes light, sometimes stiff sentences. A handful would come by to say hello or thank me heartily after a public talk. I spent time with them in pubs in Europe and bars in North America, and even had the rare opportunity to picnic with a group of them in a sun-drenched park in an area of the world—Ireland—when it was undergoing a rare two week heatwave. Although I preferred evenings in the pubs and day time picnics, I spent most of my time with them online using various chatting protocols, usually Internet Relay Chat (IRC).
As will come as no surprise, the ethical conundrums flowing out of my research were many, so many it is a theme I explore time again in the book now under works. But I can’t help but think of what anthropologist Danilyn Rutherford calls—kinky empiricism—a term she uses to define the (often tortured) nature of anthropological research. By kinky she means to convey a shape which captures the notion that knowledge is not smooth or straightforward but comes with knots and kinks. By kinky she also means to convey a spirit of “S and M and other queer elaborations of established scenarios, relationships, and things.” Foremost, she introduces kinky empiricism to portray the deeply ethical character of anthropological research: “[anthropological] methods create obligations, obligations that compel those who seek knowledge to put themselves on the line by making truth claims that they know will intervene within setting and among the people they describe.”
My obligations to Anonymous have been many and they range from writing letters to judges pleading for leniency, to translating their world to multiple publics. But the one obligation on my mind the most these days is self-imposed and it has to do with my desire to balance between two opposing forces: the rational and the mystical, the Apollonian force of empiricism and logic, and the Dionysian force of pleasure and ecstasy.
In my writings, I want to stamp out misinformation, to be critical of some of their actions, and to clear up the confusion of the so-called chaos in Anonymous; they are sensible, and must be rendered such, given that nation-states and prosecutors and judges would like to cast them as mere criminals unwilling to entertain their actions as politically motivated. But I also want to keep the magic of Anonymous alive. To disenchant them would be, in my estimation, tantamount to breaking my own moral pact and also to miss what makes them interesting.
Only with time and the judgements of others (and, hopefully, through the process of writing my book) will I know whether I have the cunning to simultaneously make chaos seem like order and order seem like chaos, the cunning necessary to give justice to Anonymous. For now, I will leave you with a rather Apollonian nugget, a report I wrote for the Center for International Governance Innovation, that seeks to stamp out some misinformation about Anonymous through a detailed, though basic, introduction to their politics and hope I can bring you some nugget of pleasure and ecstasy in the not so distant future.
It’s been nearly four years since The Asthma Files (TAF) really took off (as a collaborative ethnographic project housed on an object-oriented platform). In that time our work has included system design and development, data collection, and lots of project coordination. All of this continues today; we’ve learned that the work of designing and building a digital archive is ongoing. By “we” I mean our “Installation Crew”, a collective of social scientists who have met almost every week for years. We’ve also had scores of students, graduate and undergraduates at a number of institutions, use TAF in their courses, through independent studies, and as a space to think through dissertations. In a highly distributed, long-term, ethnographic project like TAF, we’ve derived a number of modest findings from particular sites and studies; the trick is to make sense of the patterned mosaic emerging over time, which is challenging since the very tools we want to use as a window into our work — data visualization apps leveraging semantic tools, for example — are still being developed.
Given TAF’s structure — thematic filing cabinets where data and projects are organized — we have many small findings, related to specific projects. For example, in our most expansive project “Asthmatic Spaces”, comparisons of data produced by state agencies (health and environmental), have made various layers of knowledge gaps visible, spaces where certain types of data, in certain places, is not available (Frickel, 2009). Knowledge gaps can be produced by an array of factors, both within organizations and because of limited support for cross agency collaboration. Another focus of “Asthmatic Spaces” (which aims to compare the asthma epidemic in a half dozen cities in the U.S. and beyond) is to examine how asthma and air quality data are synced up (or not) and made usable across public, private, and nonprofit organizations.
In another project area, “Asthma Knowledges”, we’ve gained a better understanding of how researchers conceptualize asthma as a complex condition, and how this conceptualization has shifted over the last decade, based on emerging epigenetic research. In “Asthma Care” we’ve learned that many excellent asthma education programs have been developed and studied, yet only a fraction of these programs have been successfully implemented, such as in school settings. Our recent focus has been to figure out what factors are at play when programs are successful.
Below I offer three overarching observations, taken from what our “breakout teams” have learned working on various projects over the last few years:
*In the world of asthma research, data production is uneven in myriad ways. This is the case at multiple levels — seen in public health surveillance and our ability to track asthma nationally, as well as at the state and county level; as seen through big data, generated by epigenetic research; in the scale of air quality monitoring, which is conducted at the level of cities and zip codes rather than at neighborhood or street level. Uneven and fragmented data production is to be expected; as ethnographers, we’re interested in what this unevenness and fragmentation tells us about local infrastructure, environmental policy, and the state of health research. Statistics on asthma prevalence, hospitalizations, and medical visits are easy to come by in New York State and California, for example; experts on these data sets are readily found. In Texas and Tennessee, on the other hand, this kind of information is harder to come by; more work is involved in piecing together data narratives and finding people who can speak to the state of asthma locally. Given that most of what we know about asthma comes from studies conducted in major cities, where large, university-anchored medical systems help organize health infrastructure, we wonder what isn’t being learned about asthma and air quality in smaller cities, rural areas, and the suburbs; what does environmental health (and asthma specifically) look like beyond urban ecologies and communities? We find this particularly interesting given the centrality that place has for asthma as a disease condition and epidemic.
*Asthma research is incredibly diffuse and diverse. Part of the idea for The Asthma Files came from Kim Fortun and Mike Fortun’s work on a previous project where they perceived communication gaps between scientists who might otherwise collaborate (on asthma research). Thus, one of our project goals has been to document and characterize contemporary asthma studies, tracing connections made across research centers and disciplines. In the case of a complex and varied disease like asthma — a condition that looks slightly different from one person to the next and is likely produced by a wide composite of factors — the field of research is exponential, with studies that range from pharmaceutical effects and genetic shifts, to demographic groups, comorbidities, and environmental factors like air pollution, pesticides, and allergens. Admittedly, we’ve been slow to map out different research trajectories and clusters while we work to develop better visualization tools in PECE (see Erik Bigras’s February post on TAF’s platform).
What has been clear in our research, however, is that EPA and/or NIEHS-funded centers undertaking transdisciplinary environmental health research seem to advance collaboration and translation better than smaller scale studies. This suggests that government support is greatly needed in efforts to advance understanding of environmental health problems. Transdisciplinary research centers have the capacity to conduct studies with more participants, over longer periods of time, with more data points. Columbia University’s Center for Children’s Environmental Health provides a great example. Engaging scientists from a range of fields, CCCEH’s birth cohort study has tracked more than 700 mother-child pairs from two New York neighborhoods, collecting data on environmental exposures, child health and development. The Center’s most recent findings suggest that air pollution primes children for a cockroach allergy, which is a determinant of childhood asthma. CCCEH’s work has made substantial contributions to understandings of the complexity of environmental health, as seen in the above findings. Of course, these transdisciplinary centers, which require huge grants, are just one node in the larger field of asthma research. What we know from reviewing this larger field is that 1) most of what we know about asthma is based on studies conducted in major cities, 2) that studies on pharmaceuticals greatly outnumber studies on respiratory therapy; that studies on children outnumber studies on adults; that studies on women outnumber studies on men; and that many of the studies focused on how asthma is shaped by race and ethnicity focus on socioeconomic factors and structural violence; finally, 3) that over the last fifty years, advancements in inhaler technology mechanics and design has been limited in key ways, especially when compared to a broader field of medical devices.
*Given the contextual dimensions of environmental health, responses to asthma are shaped by local factors. What’s been most interesting in our collaborative work is to see what comes from comparing projects, programs, and infrastructure across different sites. What communities and organizations enact what kinds of programs to address the asthma epidemic? What resources and structures are needed to make environmental health work happen? Environmental health research of the scale conducted by CCCEH depends on a number of factors and resources — an available study population, institutional resources, an air monitoring network, and medical infrastructure, not to mention an award winning grassroots organization, WE-ACT for Environmental Justice. Infrastructure can be just as uneven and fragmented as the data collected, and the two are often linked: Despite countless studies that associate air pollution and asthma, less than half of all U.S. counties have monitors to track criteria pollutants. And although asthma education programs have been designed and studied for more than two decades now, implementation is uneven, even in the case of the American Lung Association’s long-standing Open Airways for Schools. This is not to say that asthma information and care isn’t standardized; many improvements have been made to standardize diagnosis and treatment in the last decade. Rather, it’s often the form that care takes that varies from place to place. One example of what has been a successful program is the Asthma and Allergy Foundation of America’s Breathmobile program. Piloted in California more than a decade ago, Breathmobiles serve hundreds of California schools each year and more than 5,000 kids. Not only are eleven Breathmobiles in operation in California, but the program has also been replicated in Phoenix, Baltimore, and Mobile, AL. Part of the program’s success in California can be attributed to the work of the state’s AAFA chapter, and partnerships with health organizations, like the University of Southern California and various medical centers. Importantly, California has historically been a leader in responses to environmental health problem.
As we continue our research, in various fieldsites, grow our archive, and implement new data visualization tools, we hope to expand on these findings and further synthesize from our collective work. And beyond what we’re learning about the asthma epidemic and environmental health in the U.S., we’ve also taken many lessons from our collaborative work, and the platform that organizes us.
The Asthma Files is a collaborative ethnographic project focused on the diverse ways people in settings around the world have experienced and responded to the global asthma epidemic and air pollution crisis. It is experimental in a number of ways: It is designed to support collaboration among ethnographers working at different sites, with different foci, such that many particular projects can nest within the larger project structure. This is enabled through a digital platform that we have named PECE: Platform for Experimental, Collaborative Ethnography. PECE is open source and will become shareable with other research groups once we work out its kinks.
PECE has been built to support collaborative, multi-sited, scale-crossing ethnographic research addressing the complex conditions that characterize late industrialism – conditions such as the global asthma epidemic and air pollution crisis; conditions that implicate many different types of actors, locales and systems – social, cultural, political-economic, ecological and technical, calling call for new kinds of ethnographic analyses and collaboration. The platform links researchers in new ways, and activates their engagement with public problems and diverse audiences. The goal is to allow platform users to toggle between jeweller’s eye and systems-level perspective, connecting the dots to see “the big picture” and alternative future pathways.
The Asthma Files has taken us “beyond academia” in a number of ways. Ethnographically, we are engaging an array of professionals, organizations and communities, trying to understand how they have made sense of environmental public health problems. We want to document their sense-making processes, and what has shaped them; we also want to facilitate their sense-making processes – through ethnography that help them understand their own habits of thought and language, and those of others with whom they likely need to work cooperatively. For example, we’ve recently been contacted by a New Orleans housing contractor who wished to know the kind of research being done on asthma and housing in Louisiana. PECE is designed to support this, making space for different kinds of participants at different points in the ethnographic process.
We’ve also gone “beyond academia” to learn how to think about and build a digital platform to support ethnographic work. One step involved selection of the best – for our purposes, for now – online content management system. Quickly, it became apparent that most technical professionals had strong preferences, sometimes based on assessments of functionality, sometimes – it seemed – as a matter of habit. Through a long, comparative process, we ultimately decided on Plone, an open source content management system known for its security capabilities (important in creating space where groups of ethnographers can work together with material, perhaps IRB restricted, out of sight even though online), for its capacity to archive original content (such as interview recordings), and for the ways it supports our effort to nest multiple projects within a larger project structure.
Another important step, which we are still figuring out, is to hire the ongoing technical help we need for PECE. We need ongoing technical help because the platform isn’t finished, as we now envision it. But also because we want the platform to continually evolve as we continue to figure out what kinds of functionality we need to support collaborative ethnographic work. And this may be specific to each project housed on PECE. So we need on-going, ever learning relationships with people who can provide the technical support PECE requires, such as computer scientists, IT specialists, or programmers. As ethnographers, we know that technical professionals will think very differently about the work that we do. And we need to learn to work with this. We need to engage with skills and knowledges that are traditionally outside of the discipline of anthropology by taking on, in a practical way, the continual anthropological challenge of figuring out how difference works.
The Asthma Files and PECE are experiments that have taken us in many new directions – beyond academia, as well as back to basic questions about what should be considered ethnographic material, where theory is in ethnography, how ethnographic findings are best presented, etc. We keep open a call for new collaborators. Let us know if you would like to be in our mix.
Ethnographic Analytics for Anthropological Studies: Adding Value to Ethnography Through IT-based Methods
Ethnographic analytics? What’s that? In short, ethnographic analytics takes advantage of today’s technology to benefit anthropological studies, and is a great example of how science and technology can come together to help us understand and explain much about society and our human condition overall. I suggest that, using the computing power of software tools and techniques, it is possible to construct a set of useful indicators or analytics to complement the five human senses for ethnographic investigation.
Where did the idea of ethnographic analytics originate? How have ethnographic analytics been used and with what results? How can you incorporate them in your work? These are all questions I will address in the following short example of a recent study application in which ethnography and IT-based analytics complemented one another to produce insights about organizational innovation. In this blog, I will focus on one indicator that I have found very useful: an emotion indicator called the Positivity Index.
Over the past three decades, I believe it has been readily apparent that computing has entered our daily lives and especially the business world in the physical forms of desktops, laptops, tablets and smartphones. These devices are tied together with an invisible infrastructure powered by the internet, and now the “cloud,” using software applications to help us do our work, connect with others around the world, and manage many of our daily activities. Two of my colleagues, Julia Gluesing, an anthropologist and also my wife, along with Jim Danowski, a communication professor, and I thought that this new extensive information technology infrastructure could be tapped as resource to help study the diffusion of innovations in globally networked corporations. The result of our collaboration was a five year National Science Foundation (NSF) grant titled: “Accelerating the Diffusion of Innovations: A Digital Diffusion Dashboard Methodology for Global Networked Organizations” (NSF 2010). This mixed methods study provided a very real demonstration of how IT-based methods can complement and extend conventional ethnographic methods. For more detail about the study see the chapter “Being There: the Power of Technology-based Methods” in the new book Advancing Ethnography in Corporate Environments: Challenges and Emerging Opportunities, edited by Brigitte Jordan, which was recently released in 2012.
Overall, we used three software tools, Linguistic Inquiry and Word Count (LIWC), WORDij and Condor, to create a set of seven diffusion indicators or analytics that provided us guidance in selecting a sample of workers and managers for ethnographic interviews and shadowing to explore the context of engineering sub-teams who were working to deliver an innovation for a new vehicle. Working with our sponsors, the company’s legal team, and two university IRBs, we were able to collect 45,000 emails exchanged by a global innovation team working in the early stages of an automotive product innovation. With that data one of the indicators we computed was a weekly “emotion” analytic, which we called the Positivity Index, for the engineering sub-teams using the Linguistic Inquiry and Word Count software (LIWC).
Specifically, we divided the LIWC category percent “posemo” by the category percent ”negemo” to compute the Positivity Index analytic. The “posemo” category contains 407 word or word stems like: “benefit, cool, excit*, great, opportun* etc. The “negemo” category contains 499 word or word stems like: awful, damag*, miss, lose, risk* etc. For example, at the beginning of one project an electrical sub-team had a high Positivity Index about an idea they had using the words “excited potential”, “significant benefit” etc. However, after a few weeks of email exchanges with the transmission group, the Positivity Index plummeted when the combined team realized they would “miss” their deadline, and “risk” not meeting their cost targets. A listing of the LIWC 64 standard categories is available here. Research by Marcial Losada (1999) indicates that a 2.9:1 (positive to negative) ratio is needed for a healthy social system. This is referred to as the “Losada Line.”
If the positivity ratio is above 2.9:1, individuals and business teams flourish, and if it is below 2.9:1, they languish (Fredrickson and Losada 2005). High-performance teams have a positive ratio of 5.6:1 and low-performance teams ratio of 0.4:1. Moreover, there appears to be an upper limit of 11.6:1 where it is possible to have too high a positivity ratio, creating the likelihood that the team will flounder because it does not consider or ignores negative input.
We used the Positive Index to create a graph of scores over time to provide us with an initial sense of each sub-team’s progress in forming and working as a team. Some sub-teams had quite an emotional roller coaster, while the emotion in others did not oscillate nearly as much.
The graphs provided us with a handy, easily understood analytic to explore with the teams to gain a deeper understanding of the context surrounding their work. In another case, rather than email, we used meeting minutes to assess sub-team performance using emotion and found that a Positivity Index derived from minutes also provided a reliable indicator of the health of a team. Over the years, I have calculated the Positivity Index on interviews, newspaper reviews of products, letters, web sites and host of other texts. I have consistently found that it gave me an initial assessment to guide subsequent ethnographic interviews and observations. I have had some false negative readings on occasion, however. In one instance, the texts of plant safety reports described that there were “no deaths or fatalities”. In this case, the Positivity Index gave an inaccurate negative reading of the emotion; “no deaths or fatalities” for the monthly report actually was quite positive. Also, sometimes there is not enough text to generate a percent “negemo,” or negative emotion, to compute a ratio. These outliers have been few, and I now routinely calculate the Positivity Index on my textual research data.
You can try out the Positivity Index using the LIWC software for free. Note: the LIWC website does use an older engine and users will get a slight difference in the results between the Tryonline and the full LIWC version.
The web page will ask you to identify your gender and age, then paste in your text. The words in the text will be counted and a percentage calculated for 7 of the 64 LIWC categories, including self-references (“I,” “me,” “my”), social words, positive emotions, negative emotions, overall cognitive words, articles (“a,” “an,” “the”), and big words (more than six letters). LIWC does provide you with the ability to customize the dictionary with your own vocabulary as well.
My research experience has made me a fan of text analytics that can augment and enhance ethnographic methods with speed and accuracy using the natural language of participants in a very systematic manner. And best of all, the analytics, like the Positivity Index to measure the emotional content of text, are reusable and repeatable.
Fredrickson, Barbara L., and Marcial F. Losada
2005 Positive Affect and the Complex Dynamics of Human Flourishing. American Psychologist 60(7):678–686.
1999 The Complex Dynamics of High Performance Teams. Mathematical and Computer Modeling 30(9–10):179–192.
National Science Foundation (NSF)
2010 Award Abstract No. 0527487. DHB: Accelerating the Diffusion of Innovations: A Digital Diffusion Dashboard Methodology for Global Networked Organizations. Available at http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0527487. Accessed January 15, 2013.
2012 Being There: The Power of Technology-based Methods. In Advancing Ethnography in Corporate Environments: Challenges and Emerging Opportunities. Brigitte Jordan, ed. pp. 38-55. Walnut Creek: Left Coast Press, Inc.
Anthropology and science and technology studies have moved way beyond academic settings to tackle a range of issues, problems, and policies that are affecting people globally. This section provides a space to talk about conducting projects, research, and applied activities that impact the people whom we partner with to propose solutions to contemporary problems. We encourage contributions from practitioners, consultants, and researchers to talk about their experiences and exchange ideas that emerge from a variety of non-academic settings. Consider this a launching pad for promoting new ideas and connecting with others who are share similar interests and a passion for promoting social justice.