Contents
Retreat on multiply instantiated institutions
The Science of Counter Earth Workshop will unify disparate communities
around an established common interest in using empirical methods, computational techniques,
and "multiply instantiated institutions" to ask big, system-scale
questions about the design and analysis of human institutions. Multiply instantiated
institutions are modern, human-engineered, data-rich, template-constrained, replicable
social systems that are large-n, large-scale, and quantitatively comparable. The goals
of the workshop are community building and the celebration of big unifying ideas.
This event is generously being supported by the William H. Neukom Institute
for Computational Science at Dartmouth College, with additional support from the Program in Quantitative Social Science.
Event info
When: Friday, May 12 into the morning of Monday, May 15.
Where: Pierce's Inn (http://piercesinn.com)
The retreat will run through Mother's Day weekend at the comfortable and rustic
Pierce's Inn, a family-run former ski lodge 15 minutes from Dartmouth College. The
retreat will include about 15 outside invitees plus sundry day guests from the
Dartmouth community.
The structure will mix short talks with time for talking, exploring, and collaborating.
The retreat's focus on more junior researchers means no keynotes or plenary or
honoraria. Schedule below.
Participants
Maarten Bos Research Scientist, Disney Research
Social Science
"I work at Disney, AMA"— Intro blurb
"There are too many of us, we need fewer PhDs in the future" — Controversial vision of the future of social science
Ceren Budak Assistant Prof., University of Michigan
social networks, social movements, news media, charitable giving
cbudak.com
"Two truths and a lie (because who doesn't love cheesy games??!!): 1) I am a computational social science researcher, 2) I don't know how to ride a bike, 3) I am an excellent cook"— Intro blurb
"All visions for the future of the sciences of society are hard to swallow and at the same time none are"— Controversial vision of the future of social science
Grace A. Benefield Ph.D. Candidate, University of California, Davis
social networks; teams; online collaboration; communication
gracebenefield.com
I direct my boundless energy towards exploring patterns of collaboration and social networks of online groups of people. As a sucker for collaboration myself, I'm researching Wikipedia, Facebook, MMOGs, Baidu Baike (Chinese Wikipedia), Github, academic, and Korean political networks.— Intro blurb
The value of research in the social sciences and humanities may surpass that of other sciences or engineering as people struggle to understand the complex "why" of human behavior--despite the fact that we'll live in a world dominated by engineered social systems.— Controversial vision of the future of social science
Clark Bernier Ph.D. Candidate, Princeton University
sociology, organizations, communication, social networks, text analysis, hierarchies
"When I'm not exploring the world from atop a bicycle, I'm trying to understand how inequalities and hierarchies co-develop with social organizations. "— Intro blurb
"We'll get better at outcomes we measure, but much worse at knowing what it is we're really measuring and what we're not. If there's a crucial role for social science in a data-saturated world, it's at this boundary."— Controversial vision of the future of social science
Simon DeDeo Assistant Professor, Carnegie Mellon University & the Santa Fe Institute
Cognitive Science, Argument, Play, Creativity, Liberal Democracy, Digital Humanities
santafe.edu/~simon
"I'm like big data meets Isaiah Berlin."— Intro blurb
"Tribalism: norms may become more, not less, elaborate and exclusive over time." — Controversial vision of the future of social science
Rosta Farzan Assistant Professor, University of Pittsburgh
Social Computing; Online Communities; Urban Computing
rosta-farzan.net
"I have three citizenship but when people guess where I am from, is far from either one of us." — Intro blurb
"A lot of what we do as science is making ourselves happy and not necessarily making a difference in the society
"— Controversial vision of the future of social science
Benjamin Mako Hill Assistant Professor, University of Washington
Peer production, collective action, group formation, online communities, volunteer mobilization, organization, communication
mako.cc/academic/
"I study collective action in online communities and seek to understand why some attempts at collaborative production — like Wikipedia and Linux — build large volunteer communities while the vast majority never attract even a second contributor."— Intro blurb
"I think that cheap, easy, and rapid experimentation has reduced the practical importance of theory for many large platforms operators. If it's cheap enough, folks are happy to discover a relationship over and over again."— Controversial vision of the future of social science
Abigail Jacobs Ph.D. candidate, University of Colorado
Computational social science, social networks, organizations
azjacobs.com
"I'm computational social scientist studying online systems & offline organizations. I like networks, machine learning, and measuring things."— Intro blurb
"It will mostly be in industry, by practitioners, and inseparable from questions about methods, privacy and design."— Controversial vision of the future of social science
Brian Keegan Assistant Professor, University of Colorado
Computational social science; network science
www.brianckeegan.com
"Mezcal is a superior spirit to scotch"— Intro blurb
"Renaissance-style city-states and elite patronage are coming back." — Controversial vision of the future of social science
Peter Krafft Ph.D. Student, MIT
Computational social science, collective intelligence
people.csail.mit.edu/pkrafft/
"I take computational problems and turn them into theories of social interaction and society."— Intro blurb
"Understanding how society does work tells us almost nothing about how society could work."— Controversial vision of the future of social science
Saiph Savage Assistant Professor, West Virginia University
Crowdsourcing, MOOCs, Civic Computing, chatbots
www.saiph.org
"Mexico City Researcher interested in creating civic and educational technology to empower all communities to become creators."— Intro blurb
"I think we can create systems that can guide anyone, anywhere to become producers and innovators of technology. My mission is to convert everyone into creators."— Controversial vision of the future of social science
Aaron Shaw Assistant Professor, Northwestern University
collective action, peer production, online communities
aaronshaw.org
"Two of the following are (arguably) true: I helped start the Salvadoran national hockey team; I once got violently ill at a dinner with two princesses and a queen of Bhutan; I was once peed on by a beetle that caused surprisingly large, but painless skin blisters."— Intro blurb
"It might not involve Universities (but I hope it does)."— Controversial vision of the future of social science
Locals (to-date)
Jeroen van Baar visiting Ph.D. student, Donders Institute
Decision-making, morality, computational modeling, fMRI
twitter.com/jeroen_van_baar
"I study 8 reasons why people are nice to each other – number 5 will make your jaw drop!" — Intro blurb
"Recent elections around the world show that no matter how enlightened we get, we will always have a taste for epic destruction."— Controversial vision of the future of social science
Luke Chang Assistant Professor, Dartmouth College
social, emotion, computation, decision-making, brain
cosanlab.com/
"I'm drawn to ideas that combine delusions of grandeur, incomprehensible methods, and cynicism" — Intro blurb
"Philosopher kings will be armed with empiricism, computational proficiency, and implanted computers."— Controversial vision of the future of social science
Nate Dominy Professor, Dartmouth College
human evolution; primate behavior; diet; ecology; anatomy
anthropology.dartmouth.edu/people/nathaniel-j-dominy
"I promise it isn't contagious..." — Intro blurb
"network stability is a fiction"— Controversial vision of the future of social science
Seth Frey Postdoc Fellow, Neukom Institute, Dartmouth College
Cognitive science, strategic behavior, Elinor Ostrom, online communities, experiments, large datasets, institutional evolution
enfascination.com/research
"I'm a cognitive scientist and computational social scientist. I think multiply instantiated social systems are a unifying kind of idea for asking bigger questions than ever before." — Intro blurb
"Every science used to be a philosophy. Political philosophy is a source of now-empirical questions. I also think beer is a part of the scientific method."— Controversial vision of the future of social science
Eshin Jolly Ph.D. Candidate, Dartmouth College
functional brain imaging, psychology, machine learning, computational social science
eshinjolly.com
"I'm an intellectual hedo-masochist who enjoys both self-loathing about my past as a social psychology researcher, as well as to learning/applying computational techniques to better answer (social), psychological and neuro-scientific questions." — Intro blurb
"If social scientists continue to have minimal impact on the design and implementation of data/algorithm-driven systems, we're all going to end up like the folks in Wall-E or Idiocracy...start investing in Brawndo stock now."— Controversial vision of the future of social science
Jason Sorens Lecturer of Government, Dartmouth College
Federalism, decentralization, secession
"Made a career-foolish decision in grad school that caused over 2000 people to pick up and move." — Intro blurb
"Reductionism will always trump complexity."— Controversial vision of the future of social science
Description
Short of rewinding the Earth, tweaking it, and replaying its myriad alternative histories, we may never be able to apply to large-scale human social institutions the same scientific tools that have brought us so much insight into human individuals. Even Facebook and Twitter, which offer n of hundreds of millions at the scale of individuals, in some sense offer only n of 1 at the scale of the social system, bear limited power to gain rigorous mechanistic insights into large-scale institutional processes.
However, despite this almost frivolous vision, there do exist social systems that are large-n, large-scale, comparable, and amenable to quantitative study. These "multiply instantiated institutions" include online social systems like online discussion fora, MOOCs, wikis, and multiplayer game servers, but also other modern, human-engineered, data-rich, template-constrained, replicable social systems: sports teams, support groups, theme parks, business franchises.
Multiply instantiated social institutions offer a unique opportunity for philosophically literate and quantitatively savvy social scientists to creatively test ancient questions about social and political organization at scale. At this junior-focused, interdisciplinary, quantitative workshop we will discuss the successes that they have already demonstrated and map out their future scientific potential.
Schedule
| Friday, May 13 | ||
| 5:30 PM - 7:00 PM | Boundary | Arrivals |
| 7:00 PM - | Leisure & Victuals | Dinner Reception |
| Saturday, May 13 | ||
| 5:45 AM - 8:30 AM | "Leisure" | Grueling morning stroll on the AT, optional |
| 8:00 AM - 9:00 AM | Victuals | Breakfast (breakfast is for the out-of-towners, but coffee for all) |
| 9:00 AM - 9:15 AM | Recess | |
| 9:15 AM - 9:30 AM | Talk T0 | Welcome |
| 9:30 AM - 10:00 AM | T1 | Simon DeDeo |
| 10:00 AM - 10:30 AM | T2 | Ceren Budak |
| 10:30 AM - 11:00 AM | T3 | Rosta Farzan |
| 11:00 AM - 11:30 AM | Buffer & Recess | Questions & Coffee |
| 11:30 AM - 12:00 PM | T4 | Abbie Jacobs |
| 12:00 PM - 12:30 PM | T5 | Grace Benefield |
| 12:30 PM - 1:00 PM | Buffer | Questions |
| 1:00 PM - 2:00 PM | Victuals | Lunch |
| 2:00 PM - 2:30 PM | Recess | |
| 2:30 PM - 3:00 PM | T6 | Aaron Shaw |
| 3:00 PM - 3:30 PM | T7 | Mako Hill |
| 3:30 PM - 4:00 PM | Buffer & Recess | Questions & Coffee |
| 4:00 PM - 4:30 PM | T8 | Saiph Savage |
| 4:30 PM - 5:00 PM | T9 | Seth Frey |
| 5:00 PM - 5:30 PM | Buffer | Questions |
| 5:30 PM - 7:00 PM | Leisure | Go outside or something |
| 7:00 PM - 8:00 PM | Victuals | Dinner |
| 8:00 PM - | Leisure | Fun, outside, fire, couches, games, & cetera. |
| Sunday, May 14 | ||
| 8:00 AM - 9:00 AM | Victuals | Breakfast |
| 8:30 AM - 9:30 AM | Leisure | Morning walk, not grueling, still optional |
| 9:30 AM - 10:00 AM | T10 | Maarten Bos |
| 10:00 AM - 10:30 AM | T11 | Clark Bernier |
| 10:30 AM - 11:00 AM | T12 | Brian Keegan |
| 11:00 AM - 11:30 AM | Buffer & Recess | Questions & Coffee |
| 11:30 AM - 12:00 PM | T13 | Peter Krafft |
| 12:00 PM - 1:00 PM | T14 | A local or two maybe |
| 12:30 PM - 1:00 PM | Buffer | Questions |
| 1:00 PM - 2:00 PM | Victuals | Lunch |
| 2:00 PM - 6:00 PM | Projects and Planning | Work |
| 6:00 PM - 7:00 PM | Leisure | Go outside or something |
| 7:00 PM - 8:00 PM | Victuals | Dinner |
| 8:00 PM - | Leisure | Fun, outside, fire, couches, games, & cetera. |
| Monday, May 15 | ||
| 8:00 AM - 9:00 AM | Victuals | Breakfast |
| 9:00 AM - | Projects and Planning | Work |
| Boundary | Departures |
Background essay
Most research using multiply instantiated institutions (MIIs) and other large-scale social systems is organized around questions posed at the scales of the individual or, in some cases, the small group. Take, for example, most social network research. However, there are now precedents in many disciplines for using MIIs to pose questions at the scale of the institution. These precedents, being early, have the admirable quality of tackling “big ideas” and they reveal exciting research frontiers.
Research approaches representing the MII perspective have existed for decades. By definition, comparative work in political science treats nation-states as comparable and in some ways representative of the space of viable states, with the aim of gaining insight into the relative effectiveness of different approaches to large-scale governance. However, the number of nation-states is relatively small, and the unique history of each nation, combined with their inextricable histories of interactions, probably limit the ability of this approach to yield definitive insights that are widely applicable across the social sciences. Similarly, in anthropology, researchers like Robert Textor and other have organized ethnographies of between 200 and 1300 human cultures into a quantitative metaanalyses to understand how social, political, and anthropological properties of different cultures correlate across the peoples of the earth (Levinson, 1991; Murdock, 1957; Murdock & White, 1969; Textor, 1967). Meta-analyses, with their well-established advantages and drawbacks, continues to be a common approach to MIIs. For example, a comparison of hundreds of qualitative and quantitative studies of resource governance institutions, covering decades, to derive the famous “design principles” for effective self-governing resource management institutions (Cox & Arnold, 2010; Ostrom, 1991; Poteete & Ostrom, 2008).
Despite this long history of interest in MIIs, the emergence of the Internet and the revolution in computational statistical methods make them increasingly viable area of study. Virtual social systems like virtual worlds, massively-multiplayer online games (MMOs), and online communities have vastly improved the practicality of implementing studies that pose social-system-scale questions empirically. The International Forestry Resources and Institutions (IFRI) project, led by Nobel Laureate Elinor Ostrom, illustrates the difficulty of performing rigorous MII work in the real world. IFRI has collected data on the effectiveness of over 100 self-governing forest management associations, and the project has yielded many important insights at the intersection of resource management and economic governance (Gibson, Williams, & Ostrom, 2005). However, this MII accomplishment has taken 3 decades and required coordinating hundreds of researchers at dozens of institutions.
By comparison, the most prominent work on virtual social systems has posed comparably exciting questions with much less time, money, and coordination. Economist Ted Castronova reports a natural experiment on a system of MMO’s to challenge Leibniz’s “best of all possible worlds” solution to the problem of evil (Castronova, 2006). In other, more macroeconomic work, Castronova uses a multi-terabyte dataset on interpersonal trading in a virtual world to numerically validate the macroeconomic Quantity Theory of Money (Castronova et al., 2009). Working between the fields of information science and political theory, Hill and Shaw compared the 30,000 wikis of the for-profit wiki host Wikia to empirically support the Iron Law of Oligarchy, a classic philosophical argument for the inherent instability of democracy (Shaw & Hill, 2014). In my own current research on a system of many amateur-hosted video game servers, I am finding that, keeping social system “success” constant, the variety of governance styles that remain effective decreases as social systems grow from 2 to 20,000 active participants.
Internet society and technology has also made it possible to extend the methodology of the fully controlled laboratory experiment to groups of unprecedented size, making possible experimental tests of toy “organizations.” Moving past research on experimental “firms” of just four people in the lab ((Camerer & Weber, 2007; 2008)), Duncan Watts and colleagues at Microsoft Research are collecting data on dozens of “organizations” of over 20 participants to understand how organization-level interventions can help us better solve collective intelligence problems such as crisis mapping (https://youtu.be/F7vraGhKW74?t=5m12s ; also see (Balietti, Goldstone, & Helbing, 2016; Gracia-Lázaro et al., 2012; Mason, Jones, & Goldstone, 2008; Wisdom, Song, & Goldstone, 2013)).
Along with the appeal of the Internet for studying MIIs, opportunities for studying them in the real world have also increased. With their very high turnover—their ability to essential “reset” every few days—theme parks are another forum for institution-scale MII research. In work at a well-known theme park, Brown & colleagues have run large field experiments over many weeks to show how small, socially-inflected changes to pay schemes in one part of the park ripple to affect transactions elsewhere (Brown, Kappes, & Marks, 2013; A. Gneezy, Gneezy, Nelson, & Brown, 2010). Large-scale field experiments and natural experiments are increasingly common in development economics, where collaborations with governments serving large, poor, rural populations have increased the viability of comparisons across whole villages and towns. Using a more historical approach, economist Peter Leeson analyzed the journals of 18th-century ship captains to understand the emergence of institutional order in the very lawless, stressful, isolated world of pirate ships (Leeson, 2009), and Skarbek has done comparable comparative work on prison gangs (Skarbek, 2014).
Because the emergence of empirically tractable MIIs is due more to technological than disciplinary advances, representative projects have emerged independently in virtually every discipline. However, these researchers lack any unifying community and, like any methodological innovators, have often had trouble bringing broader attention to their work. This workshop, The Science of Counter Earth, will bring this diverse community together under their established common interest in using empirical methods, computational techniques, and multiply instantiated social systems to ask big, system-scale questions about the design and analysis of human institutions.
References
Balietti, S., Goldstone, R. L., & Helbing, D. (2016). Peer review and competition in the Art Exhibition Game. Pnas, 113(30), 8414–8419. http://doi.org/10.1073/pnas.1603723113
Brown, A., Kappes, J., & Marks, J. (2013). Mitigating Theme Park Crowding with Incentives and Information on Mobile Devices. Journal of Travel Research, 52(4), 426–436. http://doi.org/10.1177/0047287512475216
Camerer, C. F., & Weber, R. (2007). Experimental Organizational Economics. In the Handbook of Organizational Economics, Eds. R. Gibbons and J. Roberts. New Jersey: Princeton University Press.
Camerer, C. F., & Weber, R. (2008). Growing organizational culture in the laboratory. In C. R. Plott & V. L. Smith (Eds.), Handbook of Experimental Economics Results. Amsterdam: Elsevier.
Castronova, E. (2006). On the Research Value of Large Games: Natural Experiments in Norrath and Camelot. Games and Culture, 1(2), 163–186. http://doi.org/10.1177/1555412006286686
Castronova, E., Williams, D., Cuihua Shen, Ratan, R., Li Xiong, Yun Huang, & Keegan, B. (2009). As real as real? Macroeconomic behavior in a large-scale virtual world. New Media & Society, 11(5), 685–707. http://doi.org/10.1177/1461444809105346
Cox, M., & Arnold, G. (2010). A review of design principles for community-based natural resource management. Ecology and Society.
Gibson, C. C., Williams, J. T., & Ostrom, E. (2005). Local Enforcement and Better Forests. World Development, 33(2), 273–284. http://doi.org/10.1016/j.worlddev.2004.07.013
Gneezy, A., Gneezy, U., Nelson, L. D., & Brown, A. (2010). Shared Social Responsibility: A Field Experiment in Pay-What-You-Want Pricing and Charitable Giving. Science, 329(5989), 325–327. http://doi.org/10.1126/science.1186744
Gracia-Lázaro, C., Ferrer, A., Ruiz, G., Tarancón, A., Cuesta, J. A., Sánchez, A., & Moreno, Y. (2012). Heterogeneous networks do not promote cooperation when humans play a Prisoner’s Dilemma. Pnas, 109(32), 12922–12926. http://doi.org/10.1073/pnas.1206681109
Leeson, P. T. (2009). The Invisible Hook: The Hidden Economics of Pirates. Princeton University Press.
Levinson, D. (1991). Encyclopedia of World Cultures. G.K. Hall & Co.
Mason, W., Jones, A., & Goldstone, R. L. (2008). Propagation of innovations in networked groups. Journal of Experimental Psychology, 137(3), 422–433.
Murdock, G. P. (1957). World Ethnographic Sample. American Anthropologist, 59(4), 664–687. http://doi.org/10.1525/aa.1957.59.4.02a00090
Murdock, G. P., & White, D. R. (1969). Standard Cross-Cultural Sample. Ethnology, 8(4), 329. http://doi.org/10.2307/3772907
Ostrom, E. (1991). Governing the commons: The evolution of institutions for collective action. Cambridge University Press.
Poteete, A. R., & Ostrom, E. (2008). Fifteen Years of Empirical Research on Collective Action in Natural Resource Management: Struggling to Build Large-N Databases Based on Qualitative Research. World Development, 36(1), 176–195. http://doi.org/10.1016/j.worlddev.2007.02.012
Shaw, A., & Hill, B. M. (2014). Laboratories of Oligarchy? How the Iron Law Extends to Peer Production. Journal of Communication, 64(2), 215–238. http://doi.org/10.2307/3227338?ref=no-x-route:6e66ee25c5945f683863db3d737bdc93
Skarbek, D. (2014). The Social Order of the Underworld: How Prison Gangs Govern the American Penal System. Oxford University Press.
Textor, R. (1967). A Cross Cultural Summary. HRAF Press.
Wisdom, T. N., Song, X., & Goldstone, R. L. (2013). Social Learning Strategies in Networked Groups. Cognitive Science, 37(8), 1383–1425. http://doi.org/10.1111/cogs.12052
Pictures
- http://andspeakingofwhich.blogspot.com/2013/05/cyrus-teed-and-new-jerusalem.html
- http://nathanielrussell.com/
- http://www.davidrumsey.com/luna/servlet/detail/RUMSEY~8~1~266606~90041590:Taf--I--Sun-and-stars-?sort=pub_list_no_initialsort%2Cpub_date%2Cpub_list_no%2Cseries_no&fullTextSearch=fullTextSearch&qvq=q:planets;sort:pub_list_no_initialsort%2Cpub_date%2Cpub_list_no%2Cseries_no;lc:RUMSEY~8~1&mi=5&trs=141