“[Y]ou get what you celebrate in a free culture,” Dean Kamen (attrib. 2009).
“…intelligent failures, as the term implies, must be celebrated so as to encourage more of them” (Edmonson 2019).
“…frustrations can be vented; accomplishments and people spontaneously celebrated. In these moments, more is at play than simple information exchange” (Laloux, 2014).
In much of the literature on organizational culture, the advice is to “celebrate” this or that. The term is used as its meaning suggests: to acknowledge or affirm through some shared event. Acknowledgement and affirmation require generosity. In the academy, the term has been mostly used adjectivally: “She is a celebrated biologist;” or “Her celebrated work on X explores…” Here, however, celebrations are active and verbal. The important thing here are the three aspects that are happening at the same time in any real celebration.
“You need to not only understand your values, but celebrate them…” (Bacon, 2009).
Celebrations in your workspace entail three important aspects:
1. There is a shared social activity. This activity is meant to honor or recognize the value of something/someone. Everyone can participate as they wish. Time and resources may be spent to hold these events. Regular and irregular events break the routine of the workplace. Within the event any number of values and accomplishments can be mentioned, or the event can itself celebrate the value of being a community. Alternately, celebrations may be as simple as someone making a positive comment about someone or some activity, and everyone else nodding and smiling. Occasions where time and resources are spent are investments by the organization to its employee community.
2. This social activity requires a shared positive emotional tone from all who participate. You do not need to be the most enthusiastic person in the room, but you are expected to actually want to celebrate. Lending your sincere emotional support to the activity is a gift you give to the community. This shared emotional space also opens up the social frame for interpersonal conversations that can build trust, and improve teamwork. Even most introverts can find something to smile about.
3. This activity is meant to be shared within a community. Going out dancing alone in a night club may be your way of “celebrating life,” but here you really belong. You are meant to be here with all these other people. And that belonging is also shared. In fact, these occasions for celebrating are times when “inclusion” ups its game to signal actual belonging. This part of celebrate requires that you’ve spent some time creating community in your workplace. This usually means that you also share “community” as a value. Every time you celebrate something/someone you are also celebrating your community.
Celebrations demonstrate generosity
Celebrating starts with a clear intention: generosity. Lacking this, no event can be called a celebration, even though it may look like one (balloons, songs, whatever). Celebrations are good barometers for the health of your institutional culture. On any one day, you might not be feeling generous. That is fine, you can still participate. You may have had the painful experience of an office party where nobody is feeling generous; where everyone knows that the event is for show only; and where there is no shift in the shared emotional mood that would allow for free conversation. In a culture turned toxic, you can no longer actually celebrate; genuine generosity will seem out of place and time.
When celebrations fail, it’s time to reexamine your culture. This means that celebrating your values (and each other) is also a litmus test on how well your governance is working to help you build a community — another reason to celebrate regularly. Putting up your values on a sign by the front door is not the same as celebrating these. This goes for your academic department or lab as much as it does for a Silicon Valley start-up.
Bacon, Jono. The Art of Community: Building the New Age of Participation. Sebastapol: OʼReilly. 2009 Available At: <http://www.artofcommunityonline.org/downloads/jonobacon-theartofcommunity-1ed.pdf>.
Edmondson, Amy C. The Fearless Organization: Creating Psychological Safety in the Workplace for Learning, Innovation, and Growth. Hoboken, New Jersey: John Wiley & Sons, Inc, 2019.
Laloux, Frederic. Reinventing Organizations: A Guide to Creating Organizations Inspired by the next Stage in Human Consciousness. Nelson Parker, 2014.
“‘Culture’ is everything we don’t have to do” (Brian Eno, 1996; W Magazine)
“‘Culture’ is anything you can get better at” Bruce Caron, 2019.
All the culture that fits: exploring the work of culture to prepare to change it
PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.
We want culture in the academy to work for us, instead of against us. The many meanings of the word “culture” — each with certain claims to capture essential aspects of this spectrum of human proclivity and activity — make the task of outlining a notion of the “work of culture” also a chore of definitions. What is it about culture that can be said to do work? And what work is important for open science?
One goal of this book is to help scholars who have little or no background in the academic study of culture to gain a sufficient purchase on this notion to become confident, productive agents of culture change for their home institutions, their professional associations and research organizations, and for the academy as a global science endeavor. Like quantum mechanics and machine intelligence, the serious study of culture is not one of these “dip your toes in the shallow end” kind of endeavor. However, with a roadmap through just enough of this contested space, even tenured chemistry professors (or pick your discipline) can become bonafide organizational culture-change agents.
Getting back to basics
Beginning anthropology classes might spend a month covering the “history of the anthropological ideas of culture.” These notions developed first through colonial excursions, and then with missionaries and colonial settlers, and finally ethnographers. Courses on “organizational culture” are now required in MBA curricula and iSchools.
Arjo Klamer (2017), a Dutch economist, introduces culture to his economics class by adding two meaning domains for this word: culture as the accomplishments of a society (e.g., baroque style as a form of European culture), and culture as creative activity within sectors of the economy (the arts, architecture, music, etc.). His first meaning gives us the adjective “cultured,” applied to individuals who exemplify a certain noticeable style; while his second is where you go to when you click on the “culture” link in an online magazine or newspaper.
Culture as a process
Folks who want to use culture and culture change as a resource or a tool to change social groups describe culture as a process. They then offer a method to intercept and guide this process (Marcus and Conner, 2014). Organizational management researchers are full of advice on the culture of organizations, but usually fail to look at how this type of culture fits into the larger sense of culture’s role in society or in individual identity. Anthropologists describe cultures and how these change without intervention, but little advice on how to intentionally change this. Here, you will find both anthropological and organizational perspectives, just so you are fully comfortable that you’ve travelled the entire landscape of the term “culture.”
Do you own your culture, or does your culture own you?
“Culture is public because meaning is” (Geertz, 1973).
Much of the disputed territory for culture, whether as an object of study, or as a field for intentional change, is centered on how culture is carried more or less unconsciously by the individual. Sometimes it feels as though we’ve been “marinated” in cultural practices our entire lives: language, cuisine, music, art, and now online content. There is a part of culture that is tacit, embodied, unspoken, and non-conscious. Culture theories tell us this, and they are not wrong. This aspect of culture is often used to demonstrate how difficult it is to manage culture.
A vague, squishy word, indeed
Jean-Louis Gassée (not an anthropologist; but rather of Apple, BeOS, and Palm fame), in a blog about Intel’s “toxic culture” writes:
“Our powerful human emotions are bundled into something we call Culture, itself a vague, squishy word……Culture develops within us in a manner similar to our taste buds: Our gustatory education starts with Mother’s milk and accumulates over time. The trouble with our acquired tastes, particularly in the realm of ideas, is that they drop below our consciousness: Raw data are filtered, judged, and labeled before being passed to our conscious, ‘rational’ processes.”
Gassée is pointing out that parts of the repertoire of shared meanings, behaviors, and sentiments that people would label “cultural” are known without any explicit knowledge of how and when we came to know these; and even less ability to describe them.
Schein (2010) calls this a cultural “layer.” This layer is learned from birth at home, and then in school, and then in the workplace, where the same tacit layer proves the hardest part to change. When your company/university/agency is running on a tacit culture layer, instead of on a reflexive intentional culture layer, it is most vulnerable to becoming toxic (Deep Dive: Toxic Culture).
Science is a reflexive, interrogative activity
Fortunately, the main aspects of academy culture we are hoping to change can all be made explicit and available to reflexive rebooting. In fact, open science is not reinventing science as much as clearing away the extraneous cultural underbrush (such as journal impact factors) that has collected in the past half-century or so. Scientists can openly interrogate these practices, and collectively move away from perverse incentives, conflicts of interest, and culturally-supported bad behavior in the academy. The leading advice to Silican Valley CEOs today is to avoid “f*cking up your culture” (See also: Don’t F*ck Up Your Culture; Retrieved May 17, 2019). The academy might want to listen here.
You cannot really avoid culture if you want change
A good point is worth saying twice: you may be an open-science pioneer who is eager and intent to bring productive changes to the academy, and yet still be uncomfortable with the notion of culture. You might prefer to offer solutions (e.g., coercive rules enforced by governments and funding organizations, novel technology platforms, and manifestos — so many manifestos) that, you hope, would shape “social behavior” without needing to confront or even consider culture. You look at the term “culture” and see a morass of competing meanings, with tangled and complex implications for the use of the term. How do you defend a program to change culture when you can’t get any three people in a room to agree on what culture means?
Scientists are many things. Each of these things have something in common: a desire for precision. The “vague, squishy” term “culture” offers very little precision and a whole load of ambiguity and complexity. As a scientist, you already have your hands full of ambiguity and complexity; you are striving to understand the inherent, emergent complexity of the universe. You rely on instruments that achieve ever-better accuracy and precision to help you extract some level of near-certainty to observe your object of study.
Many scientists are dismayed by the sheer amount of fuzziness surrounding the notion of culture. So the project at hand is to un-fuzzy that corner of culture where the academy can work on intentional changes to promote open science. The rest can remain terra incognito. The fact is, you don’t need to be an anthropologist to put culture to work in your organization.
In short: the good news is that the cultural work of open science is centered on those aspects of culture that can be intentionally described, discussed, and refactored — even if some of these might later become routine and get framed as default expectations. It’s not a bad thing to have your active culture also inform the tacit level of culture, it’s actually a goal: norms are cultural behaviors and attitudes that have become tacit culture. A norm is when “we open scientists do things like this,” and think: why would we do anything else?
Culture: trimmed down to size for the open scientist
Here we will trim the semantic tangle of the term “culture” to a more specific notion of culture: to the point where it can serve our understanding of how this works and how this fits into the future of the academy. The word “culture” will still hold all of its diverse and multiplex meanings everywhere else, however, here we’ll just agree to use it in one specific way to cut through a lot of the semantic shrubbery it has acquired over the centuries and around the globe.
Learning from anthropology
We can start by looking at some general attributes of “culture.” In his 1993 book, Culture, Chris Jenks notes (following Ralph Parsons):
“…for present purposes three prominent keynotes of the discussion [around culture] may be picked out: first, that culture is transmitted, it constitutes a heritage or a social tradition; secondly, that it is learned, it is not a manifestation, in particular content, of man’s genetic constitution; and third, that it is shared. Culture, that is, is on the one hand the product of, on the other hand a determinant of, systems of human social interaction” (Jenks 1993: 59).
Lets put these verbs into the following order: learn (first exposure) → share (locally) → transmit (across space/time). Repeat as needed. This sounds a lot like education, something the academy already does. For the individual, this process is, or can be, a lifelong activity. What Clifford Geertz reminds us is that these cultural activities are public. Nothing is cultural until it is shared. That means these activities are available to study, and to change, and to be changed through intentional intervention (although somewhat less available when they are only tacit).
One easy way to see what Jenks is proposing here is to substitute “language” for “culture;” after all, language is a good part of any society’s cultural repertoire. Saying that language is transmitted is to acknowledge that we don’t need to invent our own language anew every generation. Saying language is learned explains that we acquire this through learning as children and then hone this learning throughout our lives. To say that language is shared points to a key concept: we need others to make this work; it’s called “conversation”. In many ways, language is primarily a type of sharing. Other skills and cultural content exhibit these same features.
The reverse is also true. If a language is not transmitted over time it “dies”. If a person doesn’t learn a language, they are left outside the conversations that happen in that language. And when a language ceases to be shared in everyday life (e.g., it becomes a “sacred” language that can only be spoken in certain places/times), other language forms will take over in daily life. Languages change all the time. Remember that. They manifest lifelong, tacit cultural practices, and they still change.
Culture comes in community boxes
“Community, therefore, is where one learns and continues to practice how to ‘be social’. At the risk of substituting one indefinable category for another, we could say it is where one acquires ‘culture’” (Cohen, 1985).
The usual container for a culture is called “community.” As an organization grows and governs its own cultural work, you can say that the group becomes a community. You can dive into “community” elsewhere in the Handbook (Deep Dive: Communities, Collectives, and Commons). Notions of community will also be threaded into many of the Handbook chapters.
Meaning, Symbols, and Memes; oh my!
Exactly what is learned, transmitted, and shared as culture is complicated. “Meaning” usually pops up here, together with “symbols” (meaning carriers). In many ways anything that can be learned (anything you can get better at by learning this), and that must be shared in order to make sense as something to do (write a song, choose a new fashion statement, enter a conversation, sports, theatre, etc.) becomes culture when the various meanings of that learned behavior are also shared. You cannot have your own private culture. That said, you can have a very small community with its own distinguished cultural behaviors.
Memes are symbols that have been reimagined as cultural-genetic replicators. The analogy to biology is intentional, and meme theorists also talk of culture change as evolution. Since the 1970s, meme theories have been proposed to explain how certain cultural content packages spread and persist.
“[Richard] Dawkin’s way of speaking was not meant to suggest that memes are conscious actors, only that they are entities with interests that can be furthered by natural selection. Their interests are not our interests. ‘A meme,’ [Daniel] Dennett says, ‘is an information packet with attitude’” (Gleick, 2011).
The notion of a meme is centered on the idea that humans as social beings are shaped by culture the same way their bodies are shaped by their DNA. If you want to explore memes a bit more, here’s a good introduction (by Dennett) and some good counter arguments (by Lanier). Here we will talk about meaning and symbols and culture change, but you are certainly free to talk about memes and evolution. You can also look into “cultural science,” where evolutionary cultural studies are being done.
Culture is a plural noun
Not grammatically, of course, but we have seen and continue to see around us how cultural notions, skills, and activities are typically multiple, contested, fragile, and liable to change. Individuals tend to privilege those notions, skills, and activities they have invested time to learn (so nobody wants to be forced to use a different language). However, since culture must be shared to be viable, individuals continually find themselves in conversation with others who have differing cultural inventories. Culture is like a life-long song we only sing once, and none of us has been handed the score for the next chorus. We just keep on singing, in multipart harmony.
Knowing is the intrinsic work of culture in your organization
Of course, culture is not only a noun. Humans are cultural beings. Humans have culture. Humans do culture. There is a lot of culture going on all the time. More recent takes on organizational culture reject this as being just some packet of ideas that gets passed around.Today, more than ever before, culture is viral, active, flowing (Appadurai, 1996). Today, culture is on the internet too.
The recent work of John Seely Brown, coming out of organizational knowledge theories in the mid 1990s (See: Boland Jr. and Tankasi, 1995), has added (or recovered) a cultural angle on knowledge management (Cook and Brown, 1999). Instead of organizations stewarding an inventory of knowledge objects, what they need to do is open up contexts and spaces for knowing: contexts for the transmitting, learning, and sharing between and among their participants (Thomas and Brown, 2011).
This concept was then picked up by David Snowden and others (Kurtz and Snowden, 2003), who mapped the contexts of knowing and “sense-making” into what they called the Cynefin Framework (https://en.wikipedia.org/wiki/Cynefin_framework, Retrieved May 20, 2019). This framework is largely about identifying types of knowing — and ways of deciding — in corporations, as a corrective to the prior knowledge management systems which only covered tacit and discursive knowledge objects (Wenger et al, 2002).
“The framework sorts the issues facing leaders into five contexts defined by the nature of the relationship between cause and effect. Four of these — simple, complicated, complex, and chaotic — require leaders to diagnose situations and to act in contextually appropriate ways. The fifth — disorder — applies when it is unclear which of the other four contexts is predominant” (Snowden and Boone, 2007).
The Cynefin Framework describes several domains of knowing; the core qualities of knowing are different in each of these. Knowing is an activity, an action, not a commodity, not a thing to be managed.
Knowing, or sense-making, is an intrinsic work for organizational culture. This is particularly true in the academy, where new knowledge and learning outcomes are a chief value proposition. Scientific “knowledge” is an output of shared knowing.
The challenge is that these domains are not always fully manageable, and neither are the humans that engage in knowing with each other, most particularly in the complex domain of the infinite game. Knowing is why we might learn more in a 10 minute conversation than we can from a 1000 page book. Knowing is how scientists play the infinite game with one another. You can briefly explore the infinite game by going back to the Things about science section.
Cynefin for the Academy
For now, the main take-aways from using the Cynefin Framework for the academy are the following:
First: it helps to explain the difference between doing science, talking/writing science, and telling others about science. These occur in different domains; and,
Second: it begins to describe the complex, emergent space of the infinite game. Learning this is central to building academy governance for game play. For centuries, most scientists, or earlier, natural philosophers, and before them, philosophers, played the infinite game individually. Today, science and learning is a team sport, and the academy needs to find ways to govern team play (Deep Dive: Knowing to Play the Infinite Game).
The Cynefin Framework is explored at length in Deep Dive sections on Leadership and Learning, so we will not pursue it further here, except for this: The Handbook also presents a version of the Cynefin Framework that uses three modal types of cultural activity to represent the framework’s logics (complex, complicated, simple). These modes are: festival, game, and spectacle. You will need to ask this question a lot: upon which logic does your organization base its decisions? Starting with the wrong logic will lead to bad, sometimes very bad, decisions. A lot of toxic culture in the academy is based on decisions arrived at in the wrong domain.
Festival: For those who grew up in the parts of the planet (such as most of North America) without festivals that involve actual danger, nudity, running with fire, social exposure, complex body skills, radical comedy — the various ingredients of festivity that make these events complex, emergent activities — we are not talking about the annual petunia festival here. Also note that the best intellectual conversations are like running with fire.
The Cultural Work of Social Organizations
Cultural practices and social organizations are intertwined in time and space. Social organizations are the social “appliances,” the furniture, that anchor human groups into more durable cultural contexts, which they support and are, in turn, supported by. These contexts expand our capacity for collective action, including economic and political action. Just as we do not need to—or get to—invent our own language, we don’t get to invent most of the social groups we intersect in our lives. But we can change them.
In order to pursue the intrinsic cultural work of the academy, we build communities inside organizations that use governance processes to support sharing knowing. We use can our organizations to manage other, social and economic tasks. If knowing is a dance, then community is the dance floor, and the organization is the dance hall.
In the twenty-five years since Jenks’ book, culture has seen a lot of new attention. From the portmanteau academic discipline of “cultural studies” to the cubicles of Silicon Valley start-up companies, the importance of culture for the everyday life and future prospects of societies and corporations has become a central theme. It’s high time for the academy to take a culture turn. You can help.
Now you know enough about the various aspects of culture to start rolling up your pants and wading in. You know that culture is (and must be) learned, shared, and transmitted. Most of culture is really vulnerable to intervention or substitution. Culture describes a broad range of human activities and a layer of meaning that is spread over (or under) social activities and organizations.
Knowing is an intrinsic work of culture, a primary activity for all cultural activities, but particularly for those, like science, that are involved in the infinite game. Knowing happens in more than one domain. The meanings of culture are all public. You can find them, interrogate them, and, yes, change them. That’s the next topic in the Handbook: The task: culture change.
Appadurai, Arjun. Modernity Al Large: Cultural Dimensions of Globalization. Vol. 1. U of Minnesota Press, 1996.
Boland Jr, Richard J, and Ramkrishnan V Tenkasi. “Perspective Making and Perspective Taking in Communities of Knowing.” Organization Science 6, no. 4 (1995): 350–372.
Cohen, A.P. The Symbolic Construction of Community. Chichester, Sussex: Ellis Horwood Ltd, 1985.
Cook, D.N., and John Seely Brown. “Bridging Epistemologies: The Generative Dance between Organizational Knowledge and Organizational Knowing.” Organization Science 10, no. 4 (1999): 381–400. http://www.jstor.org/stable/2640362.
Geertz, C. The Interpretation of Cultures. New York: Basic Books, 1973.
Gleick, James. The Information: A History, a Theory, a Flood. 1st ed. New York: Pantheon Books, 2011.
Jenks, Chris. Culture. London And. New York: Routledge, 1993.
“First: the asshole helps himself to special privileges in cooperative life; second: he does this out of an intrenched sense of entitlement; third: he is immunized against the complaints of other people.” Aaron James: Assholes: a Theory… the intro video (2012) <https://youtu.be/d2y-pt0makw>
Open science organizations need to achieve the status of a Zero-Asshole Zone
Depending on who you talk to, the academy’s asshole problem is either extremely dire, vastly complicated, or both. Very few people would say it doesn’t exist. The “complicated” version tries to balance assholish behaviors with some idea that the pursuit of new knowledge in a hyper-competitive environment requires a intellectual with an enhanced sense of self-confidence, an enormous ego, a thick skin, and relentless drive. Only a complete narcissist can out-compete all the other assholes in the struggle for resources and credit. Colleagues who hang around this social-black-hole personality hope to ride along in the car of his success (i.e., “He may well be an asshole, but he’s our asshole”):
“The traits associated with narcissism explain why some people have an innate ability to dominate the scene. This includes the good serious face that implicitly tells their entourage that their research is important but also their willingness to use resources without any scruples or any sense of a possible cost for the community as a whole. This provides advantages in a system that monitors production and not productivity. We can understand why these innate leaders have supporters that praise their qualities — because of their fast-track access to resources that are usually difficult to get” (Lemaitre, 2015).
This “nice scientists finish last” mind-set serves to demonstrate why open science, with fierce equality and demand sharing, is an important, and urgent, remedy for the academy. The “cost” to the community — and to your own team, lab, department, or school — of even one real asshole is greater than you might at first guess. Assholes breed more assholes as they chase away nice, clever people. “Ultimately we are all diminished when clever people walk away from academia. So what can we do? It’s tempting to point the finger at senior academics for creating a poor workplace culture, but I’ve experienced this behaviour from people at all levels of the academic hierarchy. We need to work together to break the circle of nastiness” (emphasis in the original) (Mewburn, 2015). <https://sasconfidential.com/2015/11/09/niceness/> retrieved April 9, 2019.
You can argue ideas without being an asshole
It is really important here to understand that arguments over ideas are not intrinsically assholish events. As we will see below, assholes demean other individuals; their behavior is aimed at people. They will also be abrasive and demeaning in the manner in which they defend their ideas. We’ve all witnessed this in conferences and seminars. Entire paragraphs of meeting “code of conduct” rules are meant to counteract this kind of behavior. Sutton offers this: “enforcing a no asshole rule doesn’t mean turning your organization into a paradise for conflict-averse wimps. The best groups and organizations — especially the most creative ones — are places where people know how to fight” (Sutton, 2007).
“Science advances one funeral at a time;” Max Planck (1932/2015) had other, grand theoretical, reasons to say this. It also applies to assholes with tenure. So the best thing to do is: never hire an asshole in the first place. This is the essential message of the No Asshole Rule. No matter how much of an academic star she/he might be, adding him/her to your faculty is a huge mistake, even more so when they show up already with tenure.
In a corporate environment, you can just ask a high-powered jerk employee to go be a jerk in some other corporation. CEO coaches offer a simple principle: “‘genuine collaboration and accountability for our own actions are non-negotiable if you plan on succeeding in this place’. … Get this right [as a CEO], and you will set yourself up with a culture that delivers far greater and more consistent long term success than the short term spikes delivered by a Jerk!” (Francis, 2017 <https://www.linkedin.com/pulse/high-performing-jerks-culture-crushers-matthew-francis/> retrieved April 9, 2019).
Assholes in positions of power in your organization can be sidetracked as much as possible, isolated and ignored as circumstances allow. Graduate students can be warned away, administrators can be informed, and professional associations — where these assholes are eager to get into leadership positions — can be immunized through active word-of-mouth. Remember that a single asshole can impact your organization for years.
In The Problem with Assholes, Elizabeth Cullen Dunn announced that “Anthropology has an asshole problem.” She notes, “[a]ssholery is contagious. Once people see an asshole being an asshole and winning, actually gaining power and prestige by being an obnoxious self-interested bully, it creates a huge incentive for other people to emulate that behavior. Assholery has ripple effects as it spreads in the form of disciplinary norms that not only enable, but hyper-value nasty, elitist, demeaning behavior” (Dunn, 2018 <http://publicanthropologist.cmi.no/2018/06/20/the-problem-with-assholes/> retrieved April 9, 2019). Anthropology is not alone. In a 2018 report, the National Academies note: “In a survey conducted by the University of Texas System…, about 20 percent of female science students (undergraduate and graduate) experienced sexual harassment from faculty or staff, while more than a quarter of female engineering students and greater than 40 percent of medical students experienced sexual harassment from faculty or staff” (NAS, 2018). The asshole problem is acute across the academy.
Sutton (2018 and 2007) notes that, on occasion, anyone can act assholishly. These “temporary assholes” are not the real problem. They tend to want to repair their lapses of civility, and to feel bad about their own behavior. The real problem comes from “authentic assholes.” A little later in this handbook we will talk about “dark” and “bright” core behaviors, (See: The bright and the dark) [NOTE: you are reading a draft of an essay in the Open Scientist Handbook, currently under construction]. This will allow us to unpack assholity into a small set of traits that can either be learned, or that display lasting personality disorders. Authentic assholes are also more likely to engage in an “exploitative sexual style” (Jones and Figueredo, 2013) that seeks instrumental sex with multiple partners; a trait that powers workplace harassment.
Not all assholes are born that way: lots of them are nurtured into bad behaviors on the job. The current, toxic academic culture can turn a temporary asshole into an chronic bad actor, a kind of “opportune asshole;” (or, in evolutionary culture terms, an “adaptive asshole”): someone who believes that bad behavior is expected of them and rewarded by their peers. They are happy to oblige.
This may be why so many precincts of the academy seem to be swarming with assholes (jerks, bad-actors, etc.). When you add the opportune- and temporary-assholes to the authentic ones, the numbers and their bad effects really add up. Sutton addressed this situation in an article in the Harvard Business Review (<https://hbr.org/2007/05/why-are-there-so-many> retrieved April 9, 2019). As the National Academies found, the most asshole-infested profession is medicine and medical school:
“A longitudinal study of nearly 3,000 medical students from 16 medical schools was just published in The British Medical Journal. Erica Frank and her colleagues at the Emory Medical School found that 42 percent of seniors reported being harassed by fellow students, professors, physicians, or patients; 84 percent reported they had been belittled and 40 percent reported being both harassed and belittled” (Sutton, 2007).
So, why are we surrounded by assholes? Sutton explains:
“The truth is that assholes breed like rabbits. Their poison quickly infects others; even worse, if you let them make hiring decisions, they will start cloning themselves. Once people believe that they can get away with treating others with contempt or, worse yet, believe they will be praised and rewarded for it, a reign of psychological terror can spread throughout your organization that is damn hard to stop” (Sutton, 2007).
The who is more important than the what
The good news is that the principles of fierce equality and demand sharing are diagnostic and therapeutic in finding and neutralizing assholes. Once the opportune-assholes find that their bad behavior is no longer applauded or even acceptable, they will need to self-monitor their personal interactions. When open-science norms support public acknowledgement of the asshole problem, and offer remedies for this in departments, labs, colleges, professional associations, etc.; authentic assholes will find that their toxic actions serve only to isolate and shame them (even though they may not feel this shame). Over time, when new norms take hold, and new hires bring fresh non-assholic voices into the mix, your corner of the academy can regain its fundamental civility, and you and your students can again argue theories and ideas, methods and experiments, without resorting to abuse and fear.
Working in a zero-asshole environment is significantly more pleasant and productive than toiling in the psychological minefield that even one asshole can create in your department, laboratory, agency, or college. Achieving a zero-asshole status takes a principled stance and procedural follow-through. It is a worthwhile goal for you as an open science culture-change agent to pursue. “Bear in mind that negative interactions have five times the effect on mood than positive interactions — it takes a lot of good people to make up for the damage done by just a few demeaning jerks” (Sutton, 2007).
The asshole in the mirror
A final thought here. Each of us is capable of astounding assholishness at any time. Most of us have experienced being on the receiving end on some occasions (in seminars, through peer review, at office hours) of abuse by those who control our academic fortunes, and use fear and humiliation in their critiques of our work, or of our capacities for research or teaching. We know how to do asshole; we’ve have enough training. We just need to not go there. And we need to isolate ourselves from the assholes we encounter. Sutton reminds us of this:
“If you want to build an asshole-free environment, you’ve got to start by looking in the mirror. When have you been an asshole? When have you caught and spread this contagious disease? What can you do, or what have you done, to keep your inner asshole from firing away at others? The most powerful single step you can take is to…just stay away from nasty people and places. This means you must defy the temptation to work with a swarm of assholes, regardless of a job’s other perks and charms. It also means that if you make this mistake, get out as fast as you can. And remember, as my student Dave Sanford taught me, that admitting you’re an asshole is the first step” (Sutton, 2007).
You can always take Sutton’s (2007) “asshole test” to self-diagnose. Or, if you find yourself believing that you are surrounded by idiots and that you should be recognized for your real talents and elevated into a higher level of society: you are probably an asshole, or at least, a “jerk”:
“Because the jerk tends to disregard the perspectives of those below him in the hierarchy, he often has little idea how he appears to them. This leads to hypocrisies. He might rage against the smallest typo in a student’s or secretary’s document, while producing a torrent of errors himself; it just wouldn’t occur to him to apply the same standards to himself. He might insist on promptness, while always running late. He might freely reprimand other people, expecting them to take it with good grace, while any complaints directed against him earn his eternal enmity” (Schwitzgabel, 2014 <https://aeon.co/essays/so-you-re-surrounded-by-idiots-guess-who-the-real-jerk-is> retrieved April 9, 2019).
This is a good reminder that assholes know who and what to kiss to get ahead. They may direct their assholocity at anyone/everyone equal or lesser than them in the academic scheme, and act entirely respectful and encouraging to those above them. Your dean may not know who’s an asshole, but grad-students might have a clear idea. Listen to them. And should you, in a moment of fatigue or stress lash out at your students, if you are a temporary asshole, then it’s up to you to make them know you acted poorly and regret it.
Feeling mean today? Go ahead, be mean to your data; interrogate it ruthlessly. Be cruel to your theories. Don’t look to validate them, find new ways to attack them. Be an asshole with your methodology; it’s certainly not as rigorous as it could be. Then, have some more coffee and be kind and humble with your students and colleagues.
Jones, Daniel Nelson, and Aurelio Jose Figueredo. “The Core of Darkness: Uncovering the Heart of the Dark Triad: The Core of Darkness.” European Journal of Personality 27, no. 6 (November 2013): 521–31. https://doi.org/10.1002/per.1893.
Lemaitre, Bruno. An Essay on Science and Narcissism: How Do High-Ego Personalities Drive Research in Life Sciences? Bruno Lemaitre, 2015.
NAS: Committee on the Impacts of Sexual Harassment in Academia, Committee on Women in Science, Engineering, and Medicine, Policy and Global Affairs, and National Academies of Sciences, Engineering, and Medicine. Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering, and Medicine. Edited by Paula A. Johnson, Sheila E. Widnall, and Frazier F. Benya. Washington, D.C.: National Academies Press, 2018. https://doi.org/10.17226/24994.
Planck, Max, Albert Einstein, and James Murphy. Where Is Science Going?, 1932.
Sutton, R.I. The No Asshole Rule: Building a Civilized Workplace and Surviving One That Isn’t. Hachette UK, 2007.
This is the introductory talk I presented at the 2018 SciDataCon in Botswana.
Let me begin by saying how gratified I am to be here, and to see all of you, many of whom are unmercifully jet lagged, as I know I am.
I want to thank Mark Parsons for doing all the heavy lifting to organize this session, and I thank all the speakers for their hard work. We lost a few speakers when their institutions wouldn’t support international travel… This demonstrates a situation that local academics face every time they try to travel to conferences in the North. Anyhow, with fewer talks, we will have more time for discussion.
My talk is about commoning around data resources on a global scale. Commoning, I argue is the destination that open data and science deserves.
For more than a decade, open science advocates have been building the infrastructure and the cultural sentiment to support open sharing for science objects, from ideas, to work flows, to data, publications, and peer reviews, and to whatever comes next.
One vision of what should logically come next is a move to internally-governed academy commons. I use this term in the plural here, anticipating a great variety of these, where institutions, careers, and scientific research can be fostered outside of the global marketplace.
The exvestment of academy content, careers, and communication from the global capital marketplace will require numerous experiments in alternative markets and governance schemes.
In many ways, however, it also means a return to how science operated not so very long ago, only with new opportunities provided by the internet and subsequent technologies. We are looking at science as a public good — scientists produce real public goods too, in terms of new knowledge and a better informed citizenry.
We expect taxes will pay for this, and we can support the value of science to our governments in many different ways outside of capital-market based returns. That is why we now turn to building science commons.
Most of these commons will be localized experiments — localized, that is, through specific disciplines and their internal data resource needs, through the mosaic of academy institutions and repositories and their capacities for data storage and use, through agencies and funders with their need to advance specific science outcomes, and through a range of funded research endeavors where scientists collaborate between institutions and across national boundaries.
Ideally, these commons will be localized to foster cultural innovation based NOT on importing these ideas from the global north, but rather, beginning with local voices and local cultural issues in every corner of the planet. Science is science from Gaborone to Geneva. Out of this panoply of knowledges, capabilities, and visions, academy commons can be built and internally governed across the planet. This is the task ahead for open science.
We have to be clear that we are also talking about “data-near governance” for these commons: about ownership and stewardship by and for the individuals who really need these data, about collaboratives of scientists whose particular research depends on the long-term stewardship of specific shared data resources.
Collective ownership of the stewardship practices for these data will form the infraCULTURE and governance focus for international data commons in the academy. These governance schemes will need to be negotiated with the various repositories where the data are held.
In order for these commons to reinforce each other and so to build a planetary solution, they must also follow shared design patterns and interoperable cultural norms resulting in shared standards and principles.
These patterns and norms also inform the logic of commoning.
Look around today and you can see hundreds of newly fashioned open-science programs and software platforms being fashioned by a vanguard of scientists.
These are the launchpads for our shared cultural journey into the future of open science.
Here we are in Botswana. What a wondrous country this is. I was here some decades ago and I had the opportunity to visit some of its great natural preserves. If you buy me a gin and tonic some evening, I will tell you about the time I was stalked by a lion near Shakawe up on the Okavango…
Botswana also holds a special place in current theories of commoning and sharing economies. It turns out that AfroFuturism can be found not only in a fictional nation of Wakanda, but also in the deep, first-growth, hunter-gatherer cultures of Botswana and Namibia.
An advanced form of commoning can be found in the cultural logics of the sharing practices of traditional San societies in Botswana. Recent ethnographies by James Suzman and Thomas Widlok, for example, outline two powerful cultural norms found in traditional sharing economies that are significantly absent from today’s cosmopolitan, market-based sharing economies and services, such as Uber and Airbnb.
The ethnographies describe these norms as “fierce equality” and “demand sharing.” These norms, they claim, could productively inform modern sharing economies anywhere in the world; economies that can outcompete against Uber in the long-term.
Here I claim that these norms can help propel academic commons away from the perverse market incentives that currently intercept and corrupt the scholarly process. What Yochai Benkler calls “the tyranny of the margin,” the ratcheting up of ever larger productivity demands by the marketplace: this is the lion that stalks the whole academy. This is why we need to build commons and safeguard our practices with really strong shared norms.
What might these norms look like inside the academy?
Fierce equality puts the norm of equality first, at all levels of science. And yes, this is where #MeToo and #TimesUp enter into the heart of the cultures of science. But there is more:
Fierce equality will prompt significant changes to how societies, universities, and funders view and support the science endeavor. Fierce equality militates against what Cameron Neylon calls bullshit excellence and privilege in the academy, against the gamification of careers and reputations using external metrics, such as journal impact factors, and ultimately against all forms of the “Matthew effect” that amplifies inequality in funding and recognition.
“Demand sharing” takes “open” to its logical destination: every scientist on the planet has a need to find the resources that support her research. Any scientist should be able to demand their share. This demand is not automatic, however. It’s not some academy birthright. It doesn’t come with your PHD.
The cultural workings that support demand sharing also require that each scientist be open to sharing what is most valuable to her: data, of course, and findings, but also questions and concerns, pain points and critical observations, help for others as needed, and perhaps even kindness.
It’s interesting how difficult it is to consider kindness as a core norm for science. Why is that? I’ll leave this one hanging here… It’s another talk.
Injecting the norms of demand sharing and fierce equality into the cultures of the academy will require the widespread adoption of emergent intentional and reflexive cultural practices. Refactoring infraculture takes a lot of time and work.
Why should we bother? What do we get in return?
Here is one thing:
Science has already started the technological move from a logic of arbitrary scarcity and scarce data resources to a logic of resource abundance. This move is central to Fourth Paradigm science and the future of big-data use. The challenges of and the opportunities for a science based on data abundance is what brings us all here this week.
At the same time we build the cyberinfrastructure, we also need to build the cyberinfraCULTURE to grow the practices that support active sharing, mixing, mining and reuse of data and other science objects. Science will never achieve the full potential for resource abundance by clinging to exclusive property rights and building paywalls around science objects.
In some ways, the cultural future of science may look a lot like the ancient history of the peoples of Botswana. Their advanced knowledge of their surroundings has sustained them for tens of thousands of years. So too, advances in open science can sustain the global scientific endeavor into the future.
A vision statement for this future academy might be something like this:
We envision an academy where members openly share their most important thoughts, processes, data, and findings through self-governing commons that are intent on the long-term stewardship of resources, on the value of reuse, on the absolute equality of participation, on the freedom of scientific knowledge, and the right of all to participate in discovery, and of each to have their work acknowledged, if not with praise, but with kindness and full consideration.
We are all knowledge hunter-gatherers. Through open repositories, platforms and other cyberinfrastructures we are creating a provident big-data savanna that will nourish science across the globe. Through commoning cyberinfracultures we can teach each other to govern this savanna wisely. Wielding the norms of fierce equality and demand sharing, we can secure this future for all scientists.
And, with enough coffee, I think we might all make it through this day!
This talk was generously supported by the Alfred P. Sloan Foundation
What follows is the text from an unfunded NSF proposal in 2008
We had offered to assemble a knowledge resource for NSF-funded virtual organizations to create governance systems that were “open, trustworthy, generative, and courageous” (taking the lead here from Maddie Grant and Jamie Nodder’s book: Humanize). The idea was to raise the level of knowledge and awareness of NSF program managers and funded PIs to the challenges and rewards of creating actual democratic governance when they build a community-led, volunteer-run virtual science organization. The operant word above is: “unfunded.” From recent events it looks like the NSF still could use a broader purview of the role of governance in its funded networks.
New Knowledge is Essential to guide Governance Plan Decisions for future CI Projects
Building the cyber-social-structure that supports cyberinfrastructure projects is equally important as building the information technologies. While critical-path project management might be sufficient to get the code done, it takes community engagement to get that code used. Every project that uses “community-based” research or promises to “serve a user community” needs to consider the issue of project governance outside of critical-path task management. However, a search for the term “governance plan” on the NSF website (January 5, 2008) shows that only five program RPFs (ITEST, PFC, MSP, CREST, and RDE) have ever asked for a plan for project governance. Even in these cases, governance was associated with task management, rather than community engagement/building. Other large scale NSF CI projects such as the DLESE digital library effort, which were/are centered on community-based content development, have had no requirement (nor guidance) on matters of community-based governance. The simple fact is this: the knowledge that would enable the NSF to give guidance to CI/VO projects about community governance planning and execution does not today exist.
Today, there is no place where NSF Program Managers or project PIs can go to gather the knowledge required to make an informed decision on a community based/led governance plan for a proposed project. The literature on VO project/task management and communication has grown considerably of late (See: Jarvenpaa and Leidner (1999), Monge and Desanctis (1998)). However, the role of community participation in decision making for VOs is mostly undertheorized and poorly understood. The Virtual Democracy Project will produce useable knowledge that the NSF and project PIs can use to make concrete decisions on the issue of community-based governance.
Dialogic Democracy in the Virtual Public Sphere
The Virtual Democracy Project centers its work on a novel extension of the theory and practice of “dialogic democracy,” as this occurs within virtual organizations (VO). This term was coined by Anthony Giddens, who wrote in 1994, “…it is the aspect of being open to deliberation, rather than where it occurs, which is most important. This is why I speak of democratization as the (actual and potential) extension of dialogic democracy—a situation where there is developed autonomy of communication, and where such communication forms a dialogue by means of which policies and activities are shaped.” The notion owes much to Habermas’s (1992) notion of the role of conversation in the public sphere (see also: Calhoun 1992).
Large-scale VOs (such as digital libraries and national collaboratories) are created outside of single institutions. They serve as bridges between communities and organizations. In order to be truly interdisciplinary (and/or inter-organizational, inter-agency, or international), they require an external position to their constituent groups. They become, in fact, “virtual public spheres” where discussions concerning the needs and goals of the VO must avoid collapsing into competing voices from within the various communities to which the members also belong (academic disciplines, universities, etc.). A VO of any scale engages this virtual public sphere whenever it proposes to use “community-based (or -led)” research or outreach.
Just as the Public Sphere opens up the space for dialogic democracy in the modern nation-state (Calhoun 1992), the virtual public sphere inside the VO opens up the dialogic space necessary for authentic community-based governance. How is this virtual public sphere created and sustained? How are practices within it enabled to shape policies and activities of the VO? How does this governance effort interact with the project management effort? These are questions that many VOs must face or ignore at their own risk.
Which form of governance is right for your CI effort?
A funded project’s policies and activities can be shaped and decisions made in many ways. When these are made through open communication among peers, a form of democracy is achievable. Conversations, commentaries, discussions, multiple opportunities for feedback into the decision process: practices such as these mark the emergence of a dialogic democracy within a VO. Fortunately for researchers, dialogic democracy is not a subtle, hidden practice. The implementation of community-led governance is a visible, recordable, completely reflexive event. This means that it’s absence is also markedly noticeable. Ask any member of a VO who makes the decisions for the project, and the answer will reveal the presence or absence, the strength or weakness, of dialogic democracy in that organization. Examples of strong and weak community governance in VOs are available for study.
Take, for example, two large, currently active VOs that have chosen completely different governance structures. The Federation of Earth Science Information Partners (ESIPFED) uses dialogic democracy as the basis of all of its workings. Its members spent three years creating the organization’s Constitution and Bylaws (ESIP Federation 2000). By contrast, the National Science Digital Library (NSDL), early in its founding period, chose not to embrace community-led governance, even though this was prominent in early discussions (NSDL 2001). How important is/was dialogic democracy to the work and the sustainability of VOs such as the ESIPFED and the NSDL? How much will this have an impact on future CI-funded VOs? How does the NSF manage funding when this also needs to be managed through community-based governance structures? As a part of the Virtual Democracy Project, PIs (past and present) from the ESIPFED and the NSDL will be surveyed about the role of dialogic democracy in these organizations. The Virtual Democracy Project will be the first NSF funded effort to look at the value of and evaluate the practices and the return on investment of dialogic democracy practices (or their absence) in existing VOs.
Software/services with built-in democracy features
While many social networking and peer feedback software services appear to offer functionalities that can be used as-is within community-led governance efforts, democracy places its own requirements on the channels and administration of communication resources. In addition the need for active communication among peers there is a new need for appropriate monitoring of these channels to ensure that their use is transparent and sufficient to support minority voices and sustain a record for review and for possible redress.
The Virtual Democracy Project (VDP) provides paradigm-shifting research for both social-science and computer-science research approaches. The application of the public-sphere based dialogic democracy model to “virtual public spheres” within VOs represents a novel research perspective for CI governance issues. The software services that constitute the vehicles for peer interaction need to also be democratically available for members of VOs, just as the files and folders, the rooms and chambers: the venues that inform the councils of government need to be available for citizens.
Computer scientists on the VDP team will be evaluating available social networking and peer-evaluation services to devise ways for software/services to be open to community inspection. Other software issues include maintaining the privacy of online voting records while allowing for independent validation of results, and maintaining logs of more public member contributions for proper attribution and rewards.
Geography offers a particularly useful domain for VOs that include unstructured crowd-sourcing (such as Yahoo Maps, Wikimapia, and geo-tagging on Flickr). Thousands of strangers every day add nodes and layers to Internet maps that are openly shared. The role of community -building/-governance practices that would promote reliable management of these voluntary community contributions for scientific research offers a window into the very front end of Web 2.0 development.
New IT services are generally built according to the emerging needs of users. Through the proposed research, new user needs for IT in support of dialogic communication will certainly emerge. Because of the dual requirements of privacy and attribution, one can predict that these software services will require novel thinking about database structures and security. The need for non-technical persons to have confidence that information assembled by the VO to inform its decisions is accurate and reflects the contributions of its members requires the construction of new diagnostic tools that can monitor software services to look for evidence of tampering or rigging. A whole new set of questions and concerns will inform the next generation of IT based social networking services that will need to meet new standards for use within VO governance structures.
Meeting concerns for the future of an inclusive cyberinfrastructure
This research effort will have immediate benefits for the remainder of the CI effort, as its outcomes will lead to practical guidance about which forms of governance might best be applied to any proposed CI program/project. Where the proposed effort embraces community participation, the activity of governance for community-building can be better budgeted for time and labor and also timing. Democracy also takes time. A three-year project that starts community-building in year three will probably fail in this task. The larger question of how much should a government agency spend on community-building efforts for any project also needs to be addressed. Planners and program directors will be able to turn to the cybersocialstructure.org site for decision support.
Where issues of community participation and dialogic democracy really come to the fore is in practices designed to improve and reward the efforts of underrepresented communities and individuals within VO decision making. Assuming the goal is actual inclusion of a diverse range of voices and interests in the decision process, authentic (and authenticatable) democratic processes are an obvious need and solution. The Virtual Democracy Project will explore the use of dialogic democratic practices as a feature of building a more inclusive cyberinfrastructure.
A final note, however, is that democratic practices also can inform and potentially improve communication by building community (and so, trust and identification with project goals) within the core group of PIs and Co-PIs (Wiesenfeld, et al 1999). There are potential benefits to the core task management effort that need to be considered in any cost-benefit decision.
I’ve just returned from the Summer meeting of the Federation of Earth Science Information Partners (ESIP). After nearly two decades of “making data matter”, ESIP continues to show real value to its sponsors. Indeed, the next few years might be a period where ESIP grows well beyond its original scope (remotely sensed Earth data) to tackle data and software issues throughout the geosciences. A good deal of the buzz at this year’s Summer meeting was a new appreciation for the “ESIP way” of getting things done.
ESIP champions open science at all levels, and this openness extends to everything ESIP does internally. ESIP is building a strong culture for the pursuit of open science in the geosciences, and remains a model for other volunteer-run virtual organizations (VRVO) across science domains. There are lessons learned here that can be applied to any arena of science.
I hope other agency sponsors will take note of ESIP when they propose to fund a “community-led, volunteer-run virtual organization.” In this letter I’m going to point out some central dynamics that can maximize the ROI for sponsors and enable these organizations to do their work of transforming science. One note: I am using the term “sponsor” here to designate agencies or foundations that fund the backbone organization, the staff of the VRVO. The work of volunteers is of course, not directly funded (apart from some logistic support).
The biggest picture
The real potential for any science VRVO to return value to its sponsors is realized as this organization develops into an active, vibrant community-led, volunteer-run virtual science/technology organization. To capture this value, the VRVO needs to focus on those activities that leverage the advantages peculiar to this type of organization, with special attention to activities that could not be realized through direct funding as, say, a funded research center. This is a crucial point. The real advantages that the VRVO offers to science and to its sponsors are based on the fact that it is not a funded project or center, and that the difference between it and funded centers (or facilities, or projects) is intentional and generative to its ROI.
The simple truth is that any volunteer-run organization will never be able to perform exactly like a funded center, just as centers cannot perform like VRVOs. Community-led organizations make, at best, mediocre research centers. Volunteers cannot be pushed to return the same type of deliverables as those expected by a center.
The biggest return that any VRVO will provide to its sponsors will come from circumstances where incentives other than funding are in play. In fact, adding money is generally a counter-incentive in these circumstances. Among these returns are the following:
A durable, expandable level of collective intelligence that can be queried and mined;
An amplified positive level of adoption to standards and shared practices;
An ability to use the network to create new teams capable of tackling important issues (=better proposals); and,
The ability to manage a diverse set of goals and strategies within the group, each of them important to a single stakeholder community, but all of them tuned to a central vision and mission.
Elsewhere I have outlined a larger number of such returns on investment. I continue to receive comments listing additional ones. I’ll do an updated list before the end of the year.
None of these returns can be funded directly by the sponsors, apart from supporting the backbone organization that in turn supports the VRVO. And none of these could effectively be funded through a center or other entity. They are predictable outcomes only of precisely the type of organization that the VRVO will, hopefully, achieve.
The real test for a science VRVO is to develop fully within the scope and logic of its organizational type. The concomitant test for the sponsors is to understand that sponsoring a new and different type of organization will require some new expectations and some period (a few years) of growth and experimentation to allow the virtual organization to find its own strength and limits.
Governance NOT Management
One important lesson learned at ESIP is this: governance must never be reduced to management. Funded projects and centers are managed. VRVOs are self-governed. Volunteer-run organizations are intrinsically unmanageable as a whole, and at their best. A VRVO can certainly house dozens or hundreds of small, self-directed teams where real work can be managed. ESIP “clusters” are good example. These teams can produce valuable and timely deliverables for science and for the sponsors.
The style of governance is also very important here. Attempts to shift governance away from the membership and into top-down executive- or oversight committees are always counterproductive. They give the membership a clear alibi to not care about the organization. Academics have enough alibis to not volunteer without adding this one. The members need to own the mission, vision, and strategies for the VO. Successful activities will emerge from initiatives that have been started independently and with some immediate urgency by small groups and which grow into major efforts with broadly valued deliverables. Bottom-up governance will outperform top-down management over the long term.
Science culture shifting
Probably the largest recognized impact that science VRVOs can make here—and perhaps only these can accomplish this—is to model a new, intentional cultural mode of producing science. This new cultural model will likely be centered on sharing (sharing is also one of the oldest cultural traits of science, only recently neglected). Sharing ideas. Sharing software, tools, techniques, data, metadata, workflows, algorithms, methodologies, null data, and then sharing results. Reuse needs to become a key metric of science knowledge (Cameron Neylon noted this at the original Beyond the PDF conference).
Transforming science means changing the culture of science. Science VRVOs must perform real culture work here. This is often a challenge for their sponsors, as these organizations are usually well situated at the center of the existing science culture. The key learning moments and opportunities, and perhaps the highest ROI for sponsoring a science VRVO is when this organization teaches its sponsor to change.
Three critical governance conditions any agency/foundation sponsor needs to heed.
There are three necessary conditions for an agency-sponsored, community-led organization to be accepted as legitimate by a science community.
The sponsoring agency needs to allow the community to build its own governance. Governance documents and practices are not subject to approval or even review by the sponsoring agency, apart from needing to follow standard fiduciary rules. The sponsoring agency can offer input the same way other individuals and groups do, but the community decides its own practices. The metrics for the governance are the growth of volunteer participation, and spread of community involvement, the perceived transparency and fairness of decisions, and the community’s value placed on the work being done.
The sponsoring agency has no right to review or in any way interfere with elections. All organization members have the right to run for office and to be elected.
The agency’s sponsorship is designed to help the organization grow into its potential as a volunteer-run, community-led scientific organization. The returns on investment for the agency are multiple, but do not include tasking the organization to perform specific duties, other than to improve over time.
Postscript: of course, the golden rule of any volunteer organization, new or old, is this: DFUTC.
I was recently asked why I call myself an online community “architect.” A fair question. My use of the label “architect” is meant to highlight how intentional communities, such as virtual organizations, can design, assemble, and use cultural practices to become more effective at achieving their goals and their vision.
The “unintentional” communities that we find ourselves belonging to (or resisting) in our society, from our neighborhoods and schools to our language groups and nations, use cultural practices that are grounded in longer histories and broader social structures. These represent the culture we are submerged in from birth; often they are the practices that represent our sense of identity and position in society.
These practices (and associated beliefs) are what anthropologists call “culture.” They remind us that much of this is learned and then used unconsciously, as habits and behaviors that come naturally to the enculturated members of the society. Intentional communities are made up of members that carry their own cultural habits from their society. On top of these habits, an intentional community agrees to add practices that are mutually agreed upon and available for discussion and revision.
Some intentional communities are created as counter-cultural groups, where their practices are designed specifically to conflict with those of the larger society. But many more intentional communities, from workplaces to voluntary societies and virtual organizations simply want to define their core values and to design governance practices to support these.
Often, corporations and networked communities fail to recognize that they need to develop an intentional culture to support their collaborations. They rely on the unconscious cultural habits of their members and on imposed management schemes to compel participation. Management practices can seem more effective and cheaper than the expense of building cultural practices and governance. However, in situations where corporations need to pivot quickly, or where virtual organizations need to rely on volunteers, there is no substitute for shared values supported by governance practices.
The literature on the costs and benefits of a robust corporate culture is quite large. But how can organizations gain expertise in developing intentional cultural practices? Just as a building architect is used to create an efficient and effective envelope of space, a community architect can help an organization create an envelope of practice. Every effective corporate culture is based on shared intention and honest design. It is the role of the community architect to become familiar with those design patterns that can help a new virtual organization build a robust cultural fabric to support its vision and its goals.
Photo Credit: “On The Saturday Before That” by Thomas Hawk on flickr
Building practices for an emerging governance gives your virtual organization community tools to explore how they want to govern their own participation. Too often, governance planners start by thinking of structures: committees, boards, and assemblies. The structures will emerge more organically if planners start with practices and their logic.
Twenty some years ago, anthropologist/sociologist Pierre Bourdieu wrote Le Sens Pratique (Logic of Practice). He noted that cultural activities were not simply reasoned, but also became embedded in their practice. Their performance included tacit knowledge that was not available to the performer, having been learned directly through the body. The cultural norms and skills are carried by their members without the need for reflection or conversation. This is precisely why “culture” is often considered as difficult to change.
How does this theory inform the work of building an intentional community governance? Mainly, I will propose that governance needs to “make sense,” not just as a reason-able activity, but as a practice that feels right. Because this community is intentional, its practices are available for reflection and conversation, and change. This is the real difference between culture out in the world and the culture of a company or a virtual organization. Any organization that loses the ability to direct its internal culture is trapped in a single loop of progress and error and will never learn its way out of this. Your culture belongs to you, and not you to it.
How can practices feel right? How do you know if a practice feels wrong? The main way is to create a small list of provisional core values. These become the touchstones that members use to judge how right or wrong a proposed practice feels. If “maximal transparency” is a core value, then a practice that hides disagreement is going to feel wrong. If “diversity of approach” is a core value, a practice that opens up to a great variety of inputs will feel right.
Don’t feel like these provisional core values will need to be written in stone. Make one of them “community owns its values” and encourage the members to embrace and celebrate them, changing them when they want to.
Remember that governance is not simply about decision making. There are a lot of expressive opportunities that it can enable that will help your members to embody the organization’s culture through their interactions. Governance needs to encourage leadership and resolve conflicts. It should promote best practices and reward service.
Are you ready to gather your fledgling community together and start planning a governance approach? Get them to outline a handful of key values first. Then challenge them to find practices that uplift and promote these. Then you can add in use cases and scenarios for them to build structures that use these practices. Before you know it, your community will have a first draft of their bare-bones governance scheme.
Photo Credit: Elgin County Archives, Wallacetown Women’s Institute fonds on Flickr
Decision making for your virtual organization needs to optimize the decision process and impact. If your organization relies on a wider community of unpaid volunteers, then you will need to find ways to involve this community in your decision process. Where decisions need to be made on a day-to-day basis, you will want to have paid staff with the authority to make these, and to also be accountable to the executive body of your virtual organization. Involving the wider community usually involves two complementary modes of decision making: election and consensus. For large organizations these two modes are sometimes used together in a multi-step process of delegation and consensus.
Why is consensus important? What type of consensus is the best? How do I create a culture of consensus? Previously, I outlined the arenas where staff and volunteer decision making occur, here I want to focus on the role of consensus. Consensus is primary important as a decision process where this can positively impact the quality of the decision and/or the efficacy of its outcome. The road a consensus decision opens up the discussion to include every member’s perspective and intuition. This process brings in the full range of the group’s knowledge to bear on the issue. During this discussion, aspects of the problem may be illuminated that were previously obscure. The result can be a decision that is stronger or more astute. Even when the discussion leads to a compromise, that compromise can be based on real-world limitations, and so, might avoid trouble after implementation. Where the implementation of the decision will require the active participation of the larger community (e.g., a decision to support a certain data/metadata format) consensus carries an invaluable mark of community involvement and ownership for the decision.
Just enough of a consensus
Absolute consensus may be unreasonable, given the range and interests of various stakeholder groups in the membership. If this is the case, and it would probably become evident during the start-up of the community, then some sort of “working consensus” (or rough consensus) might be a reasonable alternative. This would be a type of super-majority that would allow for a few opposing views to be not included in the final decision, but to be included in a durable report of the decision process as a minority perspective. The logic is to be able to move ahead, while maintaining the conflict that emerged in the decision process on the surface of the final decision. This type of working consensus would need to have at least a 81% majority: in a group of 20, no more than three people can disagree with the final decision. The goal is always to achieve a total consensus, with the working consensus as a fall-back.
Consensus decision making requires a consensus-aware culture for interaction within the group. There are some established cultural practice guidelines for consensus organizations. One of my favorites is the Seeds for Change organization in the UK. The consensus decision process challenges each member to listen fully to the arguments, to state their own position clearly, and to be aware that they have more than just an option to support or block a decision. A member can also abstain, withholding their outright support and refusing to block a decision. It is important in the discussions leading to a decision that the facilitator (often a staff member) is also a process mentor, reminding members of the need for open minds and hearts in the process, and a clear-headed, well-founded motive when a member decides to block a decision.
Consensus decision making does not directly scale beyond a couple-dozen members. In a larger community, each stakeholder subgroup (this requires a fractal subsetting to sub-groups of no more than a couple-dozen members) is granted a representative to an executive council where the consensus discussion is held. At the point of a vote, the representative returns to their subgroup and outlines the issues and the proposed decision. Once a consensus is acquired within the subgroup, this is carried back to the executive group.
The process of arriving at a consensus is at the same time a process of listening to the best ideas and the strongest fears of the community’s stakeholders, and a means to forge a better solution as a final decision. A decision based on consensus carries the trust and the will of the entire community.
Your virtual organization will work harder and better when everyone has a say about policies, and not just about procedures. Policy setting happens best in the second loop of a double-loop governed organization. That way the policy can respond directly to the vision of the organization.
A friend, a sysadmin at a major research university, was on his way to DEF CON when I ran into him on the street. He enjoyed hearing about the new security hacks he would be facing, and, as usual, he was not happy about the security measures on his campus. After describing how schools, departments, and centers had managed to grab the right to host their own Internet content—with predictably inconsistent results—he concluded that even his own department could use some new policies.
“Unfortunately, I can’t make policy,” he said, “I can only recommend procedures.” Faculty make policy, he explained. Staff implement this as well as they can. “I can talk all day, but some new PhD who thinks he knows enough will want to run his own server and connect into the department’s databases on my servers.” My friend has far more knowledge about computer security than he can implement, and he sees trouble ahead against which he cannot defend by making and enforcing better policies. When the system fails, when data are stolen or lost, he will be asked to explain and tasked to repair the damage. When the fan and the feces collide, he only hopes the precious work of graduate students is not collateral damage.
I could just recommend that you do not follow the model of a large academic department in a research university when you create your virtual organization. However, I doubt any of you (particularly those of you who have worked in a large academic department) had plans to do so. My point here is that every member of your organization can contribute to its policies and help defend it from failure.
Here are three ways you can make policies more effective for your organization:
1) When you create an executive panel or committee to make policy, be sure that this body is well connected with the larger membership.
2) Use a federated election process to preserve the voices of minority factions and edge groups, and empower contributions from across the membership.
3) Get additional feedback from the membership before you implement a new policy.
As a bonus, you will find that policies that are enacted with these practices are likely to be followed with greater rigor and care than those that simply appear in an email from the top.