There are books and libraries of books that talk about science: its history, sociology, philosophy, politics, and practice. As a scientist, you’ve likely gotten this far in life without reading any of these. You probably don’t need to start now. In this essay, a few remarks about science will help anchor the Open Scientist Handbook into a particular framework for science as a project, as an endeavor, and a life-way. You are already a scientist, so you don’t need a general introduction to “science.” Also, you can learn everything you need about open science as a practice by checking out the (Open Science MOOC; Accessed May 28, 2020).
This essay links into several other essays in the book that you can explore if you wish, when it’s convenient. Here you will find several Richard Feynman quotes. Do you want a good example of an open scientist? Be like Richard Feynman (who died before open science became a meme):
“If it turns out it’s like an onion with millions of layers and we’re just sick and tired of looking at the layers, then that’s the way it is, but whatever way it comes out, its nature is there and she’s going to come out the way she is, and therefore when we go to investigate it we shouldn’t pre-decide what it is we’re trying to do except to try to find out more about it” (Feynman 2005).
Nature is not entirely knowable; for very good reasons, including its emergent, adaptive complexity, and our embedded place within it (cf. Max Planck 1932/2015). Not yet knowing everything about nature and the universe is why science still exists. Nature not ever being knowable is the scientist’s best job security.
Nature is a great part of what James P. Carse (1987) called the “infinite game.” By studying nature, scientists get to be players in/with this infinite endeavor. Not many humans get to do this for a living, but all of us do this because we are alive. When we stop breathing, the infinite playing goes on without us.
Carse has a list of distinctions between “finite” and “infinite” games. Francis Kane’s New York Times (04/12/1987) review of Carse’s book says:
“Finite games are those instrumental activities - from sports to politics to wars - in which the participants obey rules, recognize boundaries and announce winners and losers. The infinite game - there is only one - includes any authentic interaction, from touching to culture, that changes rules, plays with boundaries and exists solely for the purpose of continuing the game. A finite player seeks power; the infinite one displays self-sufficient strength. Finite games are theatrical, necessitating an audience; infinite ones are dramatic, involving participants.”
Finite games and infinite play
The Handbook has a quibble about Carse’s use of the term “game” for what is really just infinite play: in this case, “science play.” Using the word “game” to describe an event with constantly changing rules and boundaries, where anyone can play and the more the better, and where the play never ends; this twists all meanings of the word “game” into unrecognizable knots. We all know what games are. They are defined by fixed rules, starting and ending points and, in many cases, specified boundaries. We play in them, and play at them, but they have real structures and definite rules that must be followed for the game to continue. Like infinite play, finite games are open-ended: their result is a future event. Unlike finite games, infinite play is neverending.
So the Handbook will use “game” for all the “finite” cases, where this matches every usual sense of the word game, and “play” for the infinite form. This echoes the older use the word “play” to signal skill and creativity. Learning to play is a common feature of cultures: play the violin, play the market. There is even foreplay (real open scientists excel at this). “Word play” gives us poetry. “Sword play” gives us corpses. “Science play” gives us knowledge of the universe. Infinite play includes breathing in and out until we can no longer do this. It’s a biological impulse to keep playing, understanding that when one must finally stop, others will continue.
The point of infinite science play is to keep playing science, to learn how to play better, and to add players to the mix; to sustain the play and the knowledge required to play at the highest levels; to change the rules, not to cheat, but to explore. In infinite play, your strengths are not what you are good at, but what you every so much want to get better at. That’s why you jumped head first into science.
Infinite play goes on even when humans are distracted by the finite games they make up to give themselves victories to distinguish their efforts. The academy can choose to invest in science play, or it can get distracted by finite games of manufactured scarcity, ersatz excellence, and cumulative advantage. This is where we are and the choice we need to consider.
Because nature is intimate within infinite play, science cannot avoid playing along. Biological evolution, for example, is a theory that describes some of the adaptive and emergent possibilities of infinite play. There is no end-point to evolution; no species really wins, some of them just have the chance to keep on playing. In fact, species extinction has a general positive effect on the robustness of the ecosystem.
There is also some discussion in the Handbook for “play,” as we know this from childhood. You can look ahead to The practical wisdom of doing science to find out how much of the wisdom you might bring to your life you learned playing as a child. Other sections include the emotional tone of doing science (Joy, Fun, and Love), which looking into playfulness as an attribute of scientific discovery. You might not be having fun yet, but if open science blossoms, who knows?
Infinite play is an intrinsically complex knowledge-management endeavor. Recent organizational management theories, such as the Cynefin Framework (Accessed May 28, 2020) started at IBM, warn that there are no “best practices” to deal with the “wicked problems” of adaptive complexity. This warning includes not just the marketplace, but also nature and culture. It turns out we are surrounded by emergent forces, and 20th Century management techniques are not up to the task. Open science mines the latest complexity theories to help guide its path.
While science methods have been addressing nature’s complexity for centuries, science knowledge-management and organizational governance have not kept up. It’s not hard to imagine science as an early-enlightenment project housed in late-medieval organizations. Open science looks to bring science governance and practice into the 21st Century.
Nature is fantastically more complex, ambiguous (despite the claims of “natural laws”), and emergent than is our ability to understand this. Here is the asymmetry that makes science infinite play, a story instead of a recipe. The amount of knowing that happens with any new science discovery is an order of magnitude greater than the description of this “finding” in a scholarly paper. That’s why any new finding is worth a thousand conversations. The record of the finding is only the scat: the knowing is the actual beast, and needs sharing.
The asymmetry of “knowing” in a room at a science conference is enormous. The room knows orders of magnitude more about the topic than does the speaker. The larger the conference, the more this unspoken knowing—this room silenced, listening to a speaker—is wasted at the event. We never need to go back to 10,000 person science meetings. Better to have five hundred small conversations, with an online platform to capture these.
This is an essay on science, not governance. Many of the sections of the Handbook offer governance guidance. Here it is only important to relate a couple major ideas.
First: your organization’s governance needs to support science play. If your department, university, or research lab is still talking about “excellence,” or “we are ranked # X!,” or “the average salary of our graduates is Y$,” you are still playing finite games.
Second: organizations that play finite games against others that use infinite play will always lose. Infinite play is a “long game.” Its players don’t care what other organizations are doing. They play to get better, not to win. Over time, they will out-innovate, out-think, and out-knowledge any peer who is chasing short-term finite wins.
Third: science is already positioned for infinite play; it gets funding from society (science goods are public goods); it holds a long-term privileged status within society; its “foe” (nature) is formidable and pushes science to ever greater tasks; its plan is flexible, it will reinvent itself as needed; its goal is just and grand: sharable knowledge of the universe.
To join into infinite play, however, science, and your workplace, needs one more thing: it needs you, and others like you, to step up and lead.
Science has never been winnable. Nobody gets to figure everything out and finish science. Every bit of new knowledge is inextricably bound with a whole lot of other bits. It is a great example of the “long game.” Likewise, any bit of learning, every insightful thought or sentence delivered in your lecture, is fully dependent on a history filled with a whole lot of other learning moments: all of which are equally fallible.
“When Socrates taught his students, he didn’t try to stuff them full of knowledge. Instead, he sought to fill them with aporia: with a sense of doubt, perplexity, and awe in the face of the complexity and contradictions of the world. If we are unable to embrace our fallibility, we lose out on that kind of doubt” (Schultz 2011).
Science looks squarely into the unknown. A scientist is never as interested in the work she has already published as she is in the next unknown she is tackling in her research. Science’s knowledge-mignardises (or petit fours: sounds better than excrement) can and have accumulated into important and useful—but still incomplete—facts and theories about our world and ourselves. And only science can do this.
“There are a lot of facts to be known in order to be a professional anything—lawyer, doctor, engineer, accountant, teacher. But with science there is one important difference. The facts serve mainly to access the ignorance…. You use those facts to frame a new question—to speculate about a new black cat. In other words, scientists don’t concentrate on what they know, which is considerable but also miniscule [sic], but rather on what they don’t know. The one big fact is that science traffics in ignorance, cultivates it, and is driven by it. Mucking about in the unknown is an adventure; doing it for a living is something most scientists consider a privilege (Firestein 2012).
Science is a “world-building” exercise; it strives to explain every-thing it contacts. There are strands of complementary knowledges or untested theoretics that could use some investigation, there are “pseudo-sciences” like Astrology, but there is no “alt-science” world. The placebo effect shows we have a lot to learn about the healing process, but does not invalidate what we know.
The main adversary to science is bad science; open science looks to remove the (perverse) incentives behind most of today’s shaky research methods and results:
“[I]n science… it is precisely when people work with no goal other than that of attracting a better job, or getting tenure or higher rank, that one finds specious and trivial research, not contributions to knowledge. When there is a marked competition for jobs and money, when such supposedly secondary goals become primary, more and more scientists will be pulled into the race to hurry ‘original’ work into print, no matter how extraneous to the wider goals of the community” (Hyde 2009).
Science rests on the possibility that everything it knows today is wrong. As Feynman noted: “Once you start doubting, just like you’re supposed to doubt, you ask me if the science is true. You say no, we don’t know what’s true, we’re trying to find out and everything is possibly wrong” (2005). Kathryn Schultz wrote an entire book on Being Wrong; science has a central spot in this work:
“In fact, not only can any given theory be proven wrong… sooner or later, it probably will be. And when it is, the occasion will mark the success of science, not its failure. This was the pivotal insight of the Scientific Revolution: that the advancement of knowledge depends on current theories collapsing in the face of new insights and discoveries. In this model of progress, errors do not lead us away from the truth. Instead, they edge us incrementally toward it” (Schultz 2011).
Science makes no claim to be right, but every claim to be the go-to method that can find out if something is wrong. From there, it harvests knowledge that has not (yet) been shown to be wrong; this is as close to being right/true as there is. And scientists get to have fun by being less-wrong today than yesterday. Scientists are passionate knowledge explorers.
“Another value of science is the fun called intellectual enjoyment which some people get from reading and learning and thinking about it, and which others get from working in it. This is a very real and important point and one which is not considered enough by those who tell us it is our social responsibility to reflect on the impact of science on society” (Feynman 2005).
“...the love he really lived for was knowing.
That thrill of first discovery returned a handful of times the next twenty years, in diminished forms. He pushed himself forward on the pleasure of first: first place, first to lay eyes on, firsts the hearts of his peer reviewers. But he wanted more than simple primacy. First was just a sporting bagatelle. To look on a thing had been true since the start of creation but never grasped until you made it so: no euphoria available to the human brain could match it. Cleaner than drugs, broader and more powerful than sex—Huxley's “divine dipsomania." Anyone who tasted it once would spend the rest of his life trying for more.
Science fit the very folds of Tom Kurten's brain. Its exuberance tempered the tedium of daily lab work, kept him alert, overrode fatigue, and rendered risks trivial. And the goal of scientific exuberance, like the goal of life, which it helped to propel, was to replicate itself (Powers 2009).”
Science is hard. It is the hardest ongoing task in all of humanity: after child rearing. One might expect society to honor, celebrate, and reward scientists for their labor.
For now, just consider that time spent doing infinite play can be intrinsically rewarding. In fact, it is potentially the most fun anyone can have. There is no video game, extreme sport, puzzle, quiz, theatre experience that can compete with those moments you expand the edge of the planet’s knowledge envelope. “You get these moments of thrill. There you are, at 3:00 in the morning, and you know something about how we evolved that nobody else in the world knows. It’s a thrill of discovery. You make this breakthrough, and you find something. It’s this wonderful, wonderful scavenger hunt when you got to the end. It’s just so great to be a scientist” (Sabeti 2008; Accessed April 11, 2019).
It is a privilege to be paid to spend your time in this pursuit. The privilege may not come with the type of salary/lifestyle society offers other occupations, but it does come with the freedom and the time to explore your own interests in nature/culture and the universe. This may be the best reason to keep the academy away from the logic of the marketplace, where freedom and time belong to others, where finite games fill your days and take you away from the very serious task of playing with nature.
Using science resources and funding for science to accomplish these things, and their like, fits extremely well into the neoliberal logic of the marketplace. The incentives and rewards are nicely lined up. These finite games have obvious winners, and lots of losers too. Here is where the Matthew effect (Merton 1988) translates into cash rewards. Nearly all the current incentives for/in the academy have perverse consequences, including patents (you can look ahead to Against Patents in the Academy). Marketplace counter-norms have already won, so it seems. Your “Research Excellence Framework” score matters a lot more than the actual new knowledge you and your colleagues have assembled.
This is why open science looks to build internal economies with its own logic, norms, principles, and rewards. There are lots of ways to be poor and have lots of money; “Money is just one of the many currencies you need to thrive and be happy in a world that requires and rewards attention, reputation, networks, learning, creativity, and tenacity….Progress in most academic disciplines now seems to move at the speed of ‘instantaneous,’ with discoveries building atop one another at a dizzying pace” (Ito and Howe 2016).
The coming logic of abundance for science arrives sooner when you manage your own expectations. Abundance starts are the edge of “enough.” Having “few needs, easily met” lets you locate a range of opportunities you might have overlooked. Here you might want to remember that open science is not just about publication access, it is about refactoring the academy to eliminate the sources for bad science, to accelerate the sharing of science objects across the planet, and to reboot the cultural DNA of academic organizations around the logic of abundance (See: Abundance).
People will ask you, “how do you incentivize scientists to do the right thing […when the wrong thing pays off so well]?” You might respond by saying something like: “how about giving scientists the means to do exceptional work, to have this work shared across the planet, to gather instant feedback from peers around the world, to live simply with plenty of time to do research without racing for funding, to have security of income and access to research tools.” Time to do what you are passionate about is a great luxury, and has been for centuries. Setting your own goals, choosing yourself as the person who can contribute and accomplish great work, mentoring others to secure the future of science: these are incentives you can own.
“Feynman always said that he did physics not for the glory or for awards and prizes but for the fun of it, for the sheer pleasure of finding out how the world works, what makes it tick” (Feynman 2005).
At this point you might be thinking that the science described in this framework is not what you wake up and do every day. Your life may be dominated by demands from your organization for high productivity scores, funded research proposals, and publications in high impact journals; editors nudging you for your peer reviews; assistant vice chancellors pestering you with patent forms to fill out; constant rejections (curse you reviewer three!) and revisions in your own output; courses to teach, lectures to prepare, and grades to give; and, right… home life. All this talk about joy and fun may seem oblique to your actual life.
Have hope. The high-pressure, low-fun career for scientists is not what science needs, and not how it was (and perhaps will not be again soon) designed to operate. We will discover below that infinite science play removes any attachment to glory as a goal. The pursuit of glory is a finite game activity, where a few get this and use it silence the many others who don’t. Some decades ago, science was considered a pursuit best done outside of marketplace incentives:
“[Vannevar] Bush convened a panel of leading academics to formulate a vision for postwar science policy. In July 1945, the panel produced a 192-page document dramatically titled Science: The Endless Frontier. Heralding basic science as the ‘seed corn’ for all future technological advancement, the report laid out a blueprint for an unprecedented union between government and academia—a national policy aimed at fostering open-ended blue-sky research on a massive scale. Though he was a conservative, Bush laid a groundwork for what Linda Marsa aptly termed a ‘New Deal for science,’ seeking to preserve a realm where university research was performed free of market dictates.
‘It is chiefly in these [academic] institutions that scientists may work in an atmosphere which is relatively free from adverse pressure of convention, prejudice, or commercial necessity,’ wrote Bush in Endless Frontier, ‘Industry is generally inhibited by preconceived goals, by its own clearly defined standards, and by the constant pressure of commercial necessity.’ Of course there are exceptions, he acknowledged, ‘but even in such cases it is rarely possible to match the universities in respect to the freedom which is so important to scientific discovery’” (Washburn 2008).
This freedom is what you’ve lost; what open science is determined to regain. You can find a lot of discussions around “academic freedom.” Being a scientist carries a great responsibility to maintain a specific variety of this. Again, here’s Feynman:
“It is our responsibility as scientists, knowing…the great progress that is the fruit of freedom of thought, to proclaim the value of this freedom, to teach how doubt is not to be feared but welcomed and discussed, and to demand this freedom as our duty to all coming generations” (Feynman 2005).
This “freedom of thought” extends to ideas shared freely within the academic community as gifts from scientists to the entire community. Hyde notes that this “gift” logic runs counter to the logic of the marketplace:
“A gift community puts certain constraints on its members, yes, but these constraints assure the freedom of the gift. ‘Academic freedom,’ as the term is used in the debate over commercial science, refers to the freedom of ideas, not to the freedom of individuals. Or perhaps we should say that it refers to the freedom of individuals to have their ideas treated as gifts contributed to the group mind and therefore the freedom to participate in that mind” (Hyde 2009).
Being a scientist means giving what you learn, the best you have, to your peers in a sharing community, with the expectation that they will do the same. It is beneficial to remember that when your mother or grandfather was doing science, the academy’s position as external to the marketplace was valorized and celebrated. Being a scientist means you can demand the freedom, the time, and the resources to investigate your own infinite play: the object of your own study and your singular passion and potential joy.
“There can be occasions when we suddenly and involuntarily find ourselves loving the natural world with a startling intensity, in a burst of emotion which we may not fully understand, and the only word that seems to me to be appropriate for this feeling is joy” (McCarthy 2015; see also Brain Pickings 2018).
Science is the most difficult, most ambitious, most challenging pursuit that the human species has ever attempted. Every unknown is integrally linked to the entire infinite playing that is the universe in which we swim. So your unknown—that bit of the game you have chosen to interrogate—is just as important as the next bit. Tackling your unknown is difficult by default (if it wasn’t this would already be a “known”). What is really painful is not being in constant, constructive contact with the five, or twelve, or a hundred other scientists somewhere on the planet who are, at this moment, running the exact same thoughts through their minds as you hold in yours.
Open science means you no longer need to consider these colleagues as your “competition.” A goal of open science is to connect you with these, your disciplinary siblings, and help you work faster, work better, and have more fun discovering more by working together than you can on your own. These are the people who can help you the most, and who need your expertise the most. Together you can make science stand up and dance through infinite play.
Doing open science means getting to dive into infinite play. Doing science means unleashing your passion for knowledge exploration and diving into your research. Doing science means sparking the same passion for learning in your students. The role of open science in your life and for your research and teaching—and through the places where you work and collaborate—is to release you from manufactured scarcity, ersatz excellence, and the quest for cumulative advantage; from all of the finite games that others use to manage your life for their goals.
“I believe that by focussing our attention on communites [sic], groups, clubs and the incentives that they work within we will make more progress, because at some level the incentives for the group are the culture” (Neylon 2015; Accessed June 25, 2019).
Almost everybody you can talk with might agree that changing culture is hard to do. Even getting your arms around the word “culture” is difficult, as we will see later in this chapter. What is becoming more obvious, in this, the opening innings of the 21st century, is that stopping culture from changing is even harder in our daily lives. Outside our jobs, we swim in world-wide jet streams of cultural ideas, and culture-informed gadgets and all the stuff we now buy at Amazon (there’s a cultural shift for you, too). Older cultural orders, such as religions and nation-states, struggle to stay current with their traditional messages.
At the same time, adopting to a new technology is often seen as trivial. We live in a stream of continuous small and large technology changes, from the internet, cell phones, and cloud services, to machine learning and artificial intelligence. We integrate these new technologies into our lives and our work as a normal course of how we operate, personally and professionally.
We spend time in new ways, connecting on social networks, joining teleconferences, editing shared documents and code, sharing ideas, photos, videos, emotional moments, personal triumphs and dead pets. How hard is it to sign up for a new platform and start sharing stories, car rides, or spare bedrooms? Not very hard at all. Today. Today, much of what we do and use was impossible until the moment it became inevitable, like Wikipedia.
Here’s the secret: every single one of these technologies that we’ve integrated into our lives has also changed our culture: the shared practices we use to learn and communicate the knowhow (and the know-where, and know-when) that technology requires to be used. A lot of culture change is just this easy. At the same time, it’s really important to note that a great part of these changes involve commercial technology platforms teaching us to become better users for their purposes; optimizing the world around their needs, instead of ours, to achieve an optimal state for their growth (See: Lanier 2014). In this case it’s not so much that we are changing culture, but rather some new variant of techno-culture is changing us.
Perhaps this is one reason some open-science promoters are hoping that all the new open-science technology platforms can simply remake us into “open scientists,” or that, when we are presented with a list of the benefits that open sharing opportunities create for the academy, we will rationally choose to hop on the open-science wagon. As if that’s all we need to do.
“The culture of today’s research universities is built from elements of past universities, including the medieval roles and responsibilities of faculty, the 18–19th century structure of departments, and the mid-20th century research funding model.” (Katz et al. 2018)
Universities already carry around a lot of historical cultural baggage, and are said to carry a profound sentiment for resisting change. “Traditions” that uphold hierarchies and concentrate power and decisions at the top are difficult to challenge from below. These need to be challenged in any case. Hundreds of open-research projects happening today across the globe are sharpening the attack.
Actually, many of the “traditions” in play today are not actually old, but rather, they reflect compromises cobbled together in prior decades to corral the growth of universities within layers of neoliberal management. “…[S]ince the eighties, Ginsberg  argues, university administrators have effectively staged a coup. They wrested control of the university from the faculty and oriented the institution itself toward entirely different purposes. It is now commonplace for major universities to put out ‘strategic vision documents’ that barely mention scholarship or teaching but go on at length about ‘the student experience,’ ‘research excellence’ (getting grants), collaboration with business or government, and so forth” (Graeber 2019).
This means, of course, that these neoliberal “traditions” mainly insinuated themselves into university cultures since World War II, which suggests they can be similarly removed through intentional cultural change tactics: through recalling and reinstating prior practices (older traditions of scientific norms and sociability—a kind of “retraditionalization” that might also be attractive to conservative culture-change skeptics); and/or replaced with practices that embrace new technologies and social justice. The point is that many of the most fiercely held traditions in the academy are not old, and are the outcomes of recent cultural changes; they are likewise open to change. In fact they are ripe for change.
“Currently, the vast majority of the science pie rewards the building of empires—that is, the model that has scientists clambering over one another to reach the top” (Steeves 2018, Springer Nature Careers, January 18).
If technology really can change our culture for its use, then using these platforms and services can help by supporting new cultural behaviors. But the real change we need to focus on is changing the intention that we, and our colleagues bring to our research. It is intent that can make an action kind or unkind; intent that colors how and why we share our research; and intent that is capable of moving the academy away from the perverse incentives that now toxify its culture. Technology alone cannot be expected to provide the cultural anchor for new, open-science behaviors.
The Work of Culture in Your Open Science Organization
“Religion is a culture of faith; science is a culture of doubt” Richard Feynman (unsourced).
“Don’t think of culture as other than accumulated learning that sits inside you as one of your layers of consciousness” (Edwin Schein 2016; Accessed April 4, 2019).
“‘Culture’ is everything we don’t have to do” (Brian Eno 1996; W Magazine)
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.
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. A recent (2017) online book for teaching anthropology in community colleges has distilled culture down to a few pages, entitled “The Culture Concept”; Accessed April 4, 2019.) 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” is a section in your newspaper/magazine/webzine
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.”
“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.
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.
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; Accessed May 17, 2019). The academy might want to listen here.
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?
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.
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 (See: on community). 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.
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.
Of course, culture is not only a noun. Humans are cultural beings. Humans have culture. Humans do culture. Science is a culture. Universities have organizational cultures. Culture is alive on the internet. 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).
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.
While this section is about the work of culture, it is good to remember that culture informs the social work of organizations. Later in this section we will look at values, virtues, freedoms, and principles, and at strategies, norms, and rules. All of these translate cultural work into social settings and systems. In some ways, social systems are like petrified conversations: they take the result of discussions and turn them into procedures, work codes, job descriptions, organizational charts, accounting schemes, etc. The important work of culture in any organization is to keep the conversations current. This is how an organization learns, pivots, when needed, and reinvents itself.
In the twenty-five years since Jenks’ book, culture has seen a lot of new attention. From the 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. 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.
“Open Science, perhaps more properly termed Open Scholarship in English, represents a culture change in the way stakeholders in the research, education and knowledge exchange communities create, store, share and deliver the outputs of their activity. For universities and other stakeholders to embrace Open Science principles, policies and practices, there needs to be a culture change in these organisations if this transition is to be successfully negotiated” (LERU 2018. Open Science and its Role in Universities: a Roadmap for Cultural Change. Advice Paper 24, May: Accessed, June 12, 2019).
“[Y]ou get what you celebrate in a free culture,” Dean Kamen.
“…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).
“You need to not only understand your values, but celebrate them…” (Bacon 2009).
In much of the literature on organizational culture, the advice is to “celebrate” values and norms. The term “celebrate” is used as its meaning suggests: first, to acknowledge with a social gathering, and second, to affirm through some shared event. Acknowledgement and affirmation require generosity. In the academy, the term has been mostly used adjectivally as an attribution: “She is a celebrated biologist;” or “Her celebrated work on X explores…”
Here, however, celebrations are active and verbal. However, balloons and song are not required. Conversations and smiles are just fine. The events can be planned or spontaneous. Large group, or small team. Day long or a momentary. Celebrations are times when you do cultural practices together, with the message that these are really what open scientists do. The important thing here are the three aspects that are happening at the same time in any real celebration.
1. There is a shared social activity.
It might be as simple as reflecting on an intentional culture practice that you are doing together. In the photograph above, participants are designing posters that show innovative projects they hope will acquire some micro-fundings. At the same time they are sharing in the open, transparent funding effort where they will know the results the next day. (See ESIP Funding Friday web page).
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 and rewards a shared positive emotional tone among 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 your 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 on your own in a night club after work may be your way of “celebrating life,” but here you belong with your team. And that sense of belonging is shared. In fact, these occasions for celebrating are times when “fitting in” ups its game to signal actual belonging. You get to be who you are. The rewards of belonging are gifts from the community to its members. This part of celebrate requires that you’ve spent some time creating community in your workplace. This usually means that you share building community as a value. Every time you celebrate something/someone you are also celebrating your community. Every sincere smile in the celebration is a gift from the community to its members.
Celebrating starts with a clear intention: generosity. Even when there is no material sharing, generosity of spirit is present. 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 very generous. That is fine, you can still participate with a modicum of generosity. Not feeling generous at all? Something might be wrong with your workplace.
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; in fact, genuine generosity will seem out of place.
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.
When celebrations succeed, they enliven conversations and diversify the work day. Putting constructive fun into your open science culture change effort is a win for everyone. Academics around you—and, confess, probably you too—have once been or are still somewhat cynical about open science changing the academy. Academics get a lot of mileage from their shared cynicism, it seems. Cynics believe change is impossible. “You’ll never incentivize academics to be generous when their career is on the line,” they say, and wait for some response they can dismiss.
When you promote incremental changes to academy behaviors, through articulating new norms and pushing for open practices, you demonstrate that change is possible, opening up the door to bigger changes, and allowing cynics to slough off their old beliefs. Shared celebrations of new practices give former cynics an experience of change (however small) and the emotional support to engage in conversations, rather than postured challenges. Some cynics become the most committed change agents when they see change happening around them.
This Handbook is designed to be used locally, and to reflect open science notions that are potentially global in scope. There are no precincts on Earth external to science. At the same time, it is just wrong to propose a single set of principles or a pre-imagined vision that locales must follow. Access to scholarly resources over the internet improves their global reach. Local or national infrastructures sustain these resources, and hundreds of academy organizations generate and steward them.
These organizations are imbedded into local education/research cultures that are the actual sites for culture change. Like a giant shoe store, the academy has a broad range of styles and sizes of organizational culture. It holds a vast inventory of different cultural attributes. And yet, to push this analogy is bit, these are still all shoes. The republic of science shares a common knowledge pool, and a collective goal. Your task, as an open-science culture-change agent is to work locally to support this planetary endeavor: science. This means that celebrating the norms of global science also opens up occasions where you can share how this is best articulated in your locale. The smallest locale you have is yourself.
The task ahead: change the culture in your university; in your professional association; in your laboratory; in your department; in your life. Yes, in your life. The changes you want to make include changes that make your institution more responsive to your needs as a scientist, and as a full person showing up to commit your life (some part of it) to the pursuit of scientific knowledge.
Even as individuals can be culture-change agents, cultural practices—particularly shared principles and norms—can, and will change individuals. Acting fiercely egalitarian means becoming fiercely egalitarian. This will have impacts on personal relationship too. Marcus and Conner (2014) call this the “culture cycle.”
“To summarize once more how the culture cycle works: Our I’s (or selves) both produce and are produced by cultures out-in-the-world, including the customs and artifacts that give shape to our daily interactions, which themselves foster and follow from cultural institutions, which in turn reflect and support our cultures’ big ideas', including ideas about what a person is and should be. Because our I’s are embedded in cultures, we cannot survive without them. In this way we are like fish in water.
Also like fish in water, we evolved an that we don’t notice culture. Indeed…culture is powerful precisely because it is usually invisible to the untrained eye. We are born into culturally saturated worlds, and seldom do we see or discuss how other worlds are arranged. Only when we travel to new places or, say, read a book about cultural psychology do we begin to understand how much culture shapes our selves and appreciate how many different forms cultures can take.”
While organizational culture may, and probably should stop short of claiming the “big ideas” of life, there are ideals, norms, and values that are big enough to share within an academy organization; like the norms of great science, and the need for practical wisdom in personal relationships. Much of the change you are looking at is in no way radical, or even novel. These changes may simply be a realignment of the behaviors of those around you (and your own) to how you’ve already imagined science should operate. In fact, the changes you make might just reduce the feelings of dissonance you have about doing science. Open science is really just asking you to be congruent with the “implicit, collective understandings about how scientific research should be done” (Anderson, et al 2007).
You still have some work to do. To succeed in changing your organizational culture you also need to work on your own person. You will need to develop resistance against those toxic aspects of current academy culture that feed bad science and bad behaviors. To change culture, you need to take science—the whole enchilada of research and teaching— personally.
“Taking it personally means changing the culture by owning our experiences and holding ourselves and others accountable (Brown 2007).”
To become a culture-change agent, you will need to celebrate the values of open science in your everyday work activities and in active conversations with others. In the process, you will want to become “authentic” with these values. While you can certainly hold additional values and cultural notions from other aspects of your life (home, religion, politics), you will be much happier when you arrive at a congruence between the open-science values you maintain on the job, and those you hold elsewhere.
“Nothing captures our understanding of moral commitment better than the way Marx astutely put it: ‘These are my principles; if you don’t like them, I’ve got others,’ (That’s Groucho Marx, in case you didn’t know)” (Benkler 2011).
“Whether you’re designing a business model, a website, or a legal statute, values are not an afterthought. Fairness is not something you attend to after the practical decisions about how to improve efficiency or innovation or productivity have been made. Fairness is integral to effective human cooperation. We care about fairness, and when we believe that the systems we inhabit treat us fairly, we are willing to cooperate more effectively” (Benkler, ibid).
“Advocates describe the Open Science ideal simply as science done right, as a public good that should be practiced in connection with society and societal values. Science done right, in this context, includes considerations of social justice and international human rights. The Open Science ideal requires researchers to pay at least as much attention to scientific responsibility as to scientific freedom. Part of that responsibility is to make the scientific literature freely available to all; but Open Science is more than open access. (Holbrook 2019)”
For the open scientist, and for open-science societies and communities, statements of strategies, norms, and rules for open science are expressions of the principles, virtues, and values of open science. Before you can start to talk about open science, you and your colleagues need to figure these out. It helps to start with a shared sense of the meanings for these concepts.
Ambiguity warning: again, these words get used in various ways. Here you will find one way to fit this all together. You might prefer other ways, but at least, here is one you can use. Let’s unpack these a bit here, starting with values. Klamer (2017) introduces values like this: “Values are qualities of actions, goods, practices, people and social entities that people find good, beneficial, important, useful, beautiful, desirable, constructive and so forth. Values are personal in the sense that individuals experience them as such and they are social in the sense that values derive their impact from being shared among groups of people.”
Values can be internal only, or shared. Individuals can value anything they wish, but shared values require cultural work to sustain. Problems arise when there are contradictions between personal and cultural values. The values you hold as an open scientist do not need to be all of your values: you have lots of other values in your life. You might be highly religious, or deeply non-religious, for example. You bring these other values with you, and they help inform the discussion over the values you choose to share in your organization.
Norms are shared values that have become universal inside the culture of your community/group. Norms inform ways of behaving that members perform without much thought, and would feel weird if they didn’t do these. Norms are the basis for being able to say, “People like us (open scientists) do things like this.” Norms are culturally stronger than rules within teams. When people like us behave like this, you do not need rules to support these behaviors.
Principles (here) are a subset of values that appear to be unquestionable; a kind of super-value that might also be linked to fundamental meanings and connections to the world. “Scientific principles” are variously described as either the fundamentals of the scientific method, constraints on science (such as falsifiability) or very basic observations of nature (water seeks its own level). In casual use, the term sometimes overlaps with “laws.” It is time to get more precise about this term.
“Fairness” is a principle that is often articulated though values such as “equity.” The “open” part of “open science” is a value that is also a principle. Other values add facets of meaning to the principle of “openness.” “Open” also unpacks to contain other values: findability, accessibility, sharability, etc.. Building a list of values often reveals common principles that they share. Being “principled” (as a person or a community) means that you are true to your principles/values. There is a lot of semantic overlap between “principles” and “norms.” Norms describe the behaviors (including attitudes) that are informed by shared principles/values.
The Open Science MOOC has a whole module on open-science principles, as these have been articulated by several organizations. You can use these examples to create your own list of values/principles. But do create your own; then own these and celebrate them. In this work we point to two principles that serve to distinguish open science to non-open science: fierce equality (Fierce Equality) and demand sharing (Demand Sharing). When these become norms, they might just be called “equality” and “sharing”.
“Prudence is a virtue, as is temperance, courage and justice. These are the so-called cardinal virtues that we find in the Nichomachean Ethics of Aristotle. Together with the theological virtues faith, hope and love, they constitute the seven classical virtues” (Klamer 2017).
“Management is doing things right; leadership is doing the right things” (Drucker 2001).
Virtues are values that have ethical meaning for you. These are not simply good to hold/do because they make sense; they are good to hold/do because they are the right thing. Virtues are not limited to just those found in books. You can articulate your own.
You can make a virtue from any value you hold as an ethical position. For example, dietary value choices might be virtues. For example: “I would never eat meat” expresses a virtue assuming you consider this an ethical decision. In contrast, other dietary choices might be aesthetic values (“I only drink single malt whisky”); or they can have a medical reason (“I’m allergic to peanuts”). These are not potential virtues.
A virtue that needs a lot of work in the academy is kindness (See: Kindness). The idea that kindness might not be essential for the academy should be seen as bizarre. All learning happens through the kindness of shared knowing. The lack of kindness as a virtue has been linked to idealized hyper-masculinity (and the associated lack of ability/inclination to do emotional labor) (Schultz 2003) and hyper-competitiveness. Both of these are toxic for the academy. if your organization is ignoring or violating its virtues, you have a real problem. Shared virtues, like other shared values, can, over time become norms in the culture of a community. People like us open scientists hold these virtues.
“It is our responsibility as scientists, knowing the great progress and great value of a satisfactory philosophy of ignorance, the great progress that is the fruit of freedom of thought, to proclaim the value of this freedom, to teach how doubt is not to be feared but welcomed and discussed, and to demand this freedom as our duty to all coming generations” (Feynman et al 2005)
“Academic freedom” is larger, older, and more fundamental as a principle than the movement to open science. This freedom has also been abused in places (such as autocratic governments) and for purposes (neoliberal logics) that obstruct the academy’s defense of this, its primary principle. The fundamental nature of academic freedom was written into the Magna Charta Universitatum on the 900th anniversary of the founding of Bologna University, and signed by more than 700 universities across the globe.
Open science is another weapon in the defense of academic freedom. The pursuit of demand sharing promotes the free flow of research objects across nations; the shepherding of any/all research within sustainable repositories; and the demand for state support to maintain and improve these resources. The pursuit of fierce equality promotes wide access to academy resources, and inclusion of research findings from all persons.
Along with its values and principles, its standards and norms, open science may also include certain new freedoms similar to those presented by the open-source software movement. (See: The Free Software Definition <https://www.gnu.org/philosophy/free-sw.html>; Accessed May 15, 2019).
This brings up the question: is open science also “free science” (free as in “speech” not as in “beer”)? Since the scope of open science is available for debate and to local formations, there is no universal answer to this question, but there are some ideas that might inform these formations.
One leg of open science is “open access” to research objects. Peter Suber; Accessed May 15, 2019; see also Suber 2012) offers an excellent overview of this topic. He notes that the current push for open access does not require “universal access” in this, its initial moment. Today, open access offers an alternative to paywalled subscription access to academy resources. When you discuss open science with others at work, you will need to decide the scope of open access your organization would like to promote. So let’s explore this scope a bit. You will have your own conversations over freedoms as these are implied and supported by open science (or libra science).
The freedom to access academy resources from anywhere. We do have the internet.
The freedom to interrogate the methods/data/software of any research result in the system. Access is a precondition of this.
The freedom to reuse academy resources.
The freedom to add to the academy’s corpus of research objects; subject to the rules of the repository applicable to all (e.g., provision of data).
The freedom to copy, mine, and analyze collections of research objects.
The freedom to be kind to one another in all actives of the academy.
The freedom to request help and receive kindness.
The freedom to participate equally in conversations, discussions, and online forums.
The freedom to always choose to do the right thing now, and not delay moral action.
The freedom to point out infractions of community rules and principles without retaliation.
The freedom to express the joy of doing science play.
Add your own freedoms to this list. And remember that freedoms are worth fighting for, as Toni Morrison reminds us.
“There may come a time when we—students, faculty, administrators, artists, and parents—will have to fight hard for education, fight hard for uncorrupted science (not the ideological or racist science); for sound social history, apolitical anthropology (not strategies of control); for the integrity of art (not its celebrity).
There may indeed come a time when universities may have to fight for the privilege of intellectual freedom” (Morrison 2019).
Discussions of open science as a movement toward social justice practices within science, and societal justice outcomes as a concern for science should be a prominent aspect, and an active conversation, of how you arrive at fierce equality in your open-science organization. Grahe et al (2020) is a good starting place to pick up the concepts of justice in/through the academy.
In building or changing the culture of your organization, the first, and an ongoing, task for you and your organization is to discuss and agree upon the values you want to share. The process of culture change in your organization begins with a discussion about values, then it builds statements that support these built as strategies, norms, and rules. Then it looks at how things get done, at the practices that apply to getting to decisions and doing work, and realigns these behaviors with its shared value statements. After that, members of the organization continue to refactor how things get discussed, decided, and done, molding processes and behaviors to satisfy not just the boundaries of these values, but to express and defend their core principles. If you skipped The Work of Culture (above), you might want to take a look. Over time, these behaviors become shared norms. People like us open scientists here would not think of doing anything else. The whole process of how to do this is described below.
“So it’s kind of like if your house catches on fire. The bad news is there is no fire brigade. The good news is random people apparate from nowhere, put out the fire and leave without expecting payment or praise. …I was trying to think of the right model to describe this form of random acts of kindness by geeky strangers. …You know, it’s just like the hail goes out and people are ready to help. And it turns out this model is everywhere, once you start looking for it” Jonathan Zittrain, Ted Talk 2009.
There are lots of ways that the rational, logical, hyper-competitive, winner-take-all, zero-sum, prisoner’s dilemma, nice-guys-finish-last, single-bottom-line, annual-productivity ratchet—or add your adjective here—mindset is just wrong for sustaining the academy and bad for science. For decades now, the same neo-liberal economic schemes that have been used to reshape how governments budget their funds have also made dramatic and disturbing inroads into university budgets and governance. Open science can show how that trend is a race to the bottom for universities. What do you say, we turn around and go another way?
“I have learnt silence from the talkative, tolerance from the intolerant and kindness from the unkind.” Khalil Ghibran, Sand and Foam.
The banishment of kindness as a necessary part of being an academic,—just one more feature of adopting the neoliberal marketplace logic, and another effect of hyper-masculinity in the workplace—allows academics to defer judgements about kindness:
“We want to argue, however, that although kindness is a commonplace in pedagogical encounters, easily recognisable by its presence or absence, attending to it can be subversive of neo-liberal assumptions that place value on utility and cost above other human values” (Clegg and Rowland 2010).
The word for kindness in Latin is humanitas: kindness makes us human. “[T]he Roman Emperor Marcus Aurelius, a leading Stoic philosopher, speaks of kindness as ‘mankind’s [sic] greatest delight’ (Philips and Taylor 2009, 18). In Aristotle’s teachings, kindness is a component of phronesis: an entire type of “practical wisdom” that we’ve slowly devalued over the past 300 years (Juarrero 1999) [ and you can blame Hume and Kant and all the usual suspects for this]. Phronesis combines virtue with a notion of adult comprehension: a way of knowing the right thing to do in all circumstances. It has little to do with intellection, and everything to do with broad experience and learning.
“Kindness is not deference, not conflict-aversion, not niceness or politeness. It's a quality of grounded, dignified, powerful warmth. It's the acumen that allows you to see other people with exquisite precision, and to know that you love them in detail” (Academics Taking Action 2018) [Lab Notes on Power in Academia <http://sophiatintori.com/zine/readable_concatenated.pdf> Accessed October 3, 2019].
The road to a doctorate is long and difficult, and so adding another layer of learning to the process might seem short-sighted. And yet avoiding learning phronesis in your daily life is probably not any easier than practicing this, since the absence of phronesis leads to serial mistakes in moral and practical judgement, any one of which can be “career defining” in a negative sense. “Practical wisdom” is integral to “doing the right thing” while you learn to “do the thing right.” Doing the right thing often includes knowing how to exercise kindness with others.
A child can show kindness, and we welcome this. An adult (one who has learned some phronesis) can act in ways that are kinder than a child, because this adult is experienced in a broader range of social circumstances and personal relationships. An adult can be—to use the Yiddish—a mensch. And a mensch can be kinder than a non-mensch or a pre-mensch.
Real kindness begins with a clear intention. This adds an important aspect of self-judgement to its base. Without this aspect you cannot actually be kind, even if others might interpret what you are doing as being kind. How do you actually judge your intentions, particularly in relationships with other people and things? Something to contemplate. Also note: Clegg and Rowland (2010) remind us that kindness is not equated with leniency or “being nice.” Real kindness uses courage to articulate accurate observations and open learning moments that can be difficult and painful for both parties.
Kindness is a normative human practice in a wide range of social frames: parenting, friendship, governance, teaching, caregiving, civil interactions. Zittrain (above) reminds us that the internet was built on kindness and generosity.
In nearly every human social endeavor, kindness matters. Even in highly-competitive sporting events, “sportsmanship” is highly valued, and is actually an internal normative form of kindness. Why should kindness, and critical interrogations about its role, be absent from research and management in the academy?
Like rationality, kindness is a form of practice, not an emotion. You can no more “feel” kind than you can “feel” rational. Unlike rationality, kindness necessarily involves others: their perspectives and needs. Kindness can and will also be judged by others for its qualities. Is it genuine? Is it motivated by a need to be perceived as kind? Is it effective in performing its intention? What is its intention? In the academy where intellectual judgements run wide and deep, kindness opens up another opportunity to be judged. But so does being unkind. Or it should. For decades, the lack of kindness in our research institutions and workplaces has gone unremarked. It is time to remark these.
Again, kindness begins with intention. The same activity with different intentions can be a kind, caring conversation, or it can be a cruel interrogation. Intentions are themselves colored by culture. Culture provides a layer of shared meaning/learning that helps the individual (both the intend-er and the intend-ee) discover and interpret shared meaning as intended. You and the other person can answer the question: what did you mean?
The social world always contains this layer of culture. There is no society without it. Individuals hold this layer as a shared/learned resource. The cultural values you bring to your open science organization can assemble the meanings that add clear intentions to shared kindness. Just as some institutional cultures today—and inside the academy—support bullying and demeaning actions (NAS et al. 2018).
One feature of kindness is that it enables both halves of the double meaning of the term “care.” To really care about someone or something, you need to tap into genuine kindness. To care for someone or something can merely be a job. But this job is also reduced without the impulse of kindness. That is why it is time to…
“[B]y infusing bureaucratic maintenance work with an ethic of care, we can challenge contemporary workplace attitudes surrounding “productivity” and “efficiency,” moving toward the recognition of maintenance itself as a valued contribution. We can also broaden access to systems of information, thereby supporting its generative value…” (Maintainers et al. 2019).
The Maintainers <http://themaintainers.org/> extend an ethic of care to each other and to their work: they keep everything running, instead of inventing new stuff. This ethic is born in kindness, and requires a level of humility not casually found in the academy, where intellectual heroics overshadow moral choices.
Nell Noddings, who is a “care theorist,” someone who makes “the caring relation basic in moral theory” (2003), looks to recenter care as a normative behavior in education and the academy. She also separates the care that is expected in work (for example, doing something really well, or managing the needs of a student/patient) as a conformity to a workplace ethic, from caring: human acts “done out of love and natural inclination” (Noddings 1988). What really works—in teaching and learning, and in team dynamics for collaborative research—is not completing the task of due-diligence, but rather building a framework of mutual caring nurtured from authentic kindness.
Bringing care into this discussion has now moved us away from communities, cohorts, and institutions. Care directs us back to intentions that are articulated in culture, but which also speak to being human in a mutually responsible human environment: a phrase not usually descriptive of the academy. “[W]e are led to redefine responsibility as response-ability, the ability to respond positively to others and not just to fulfill assigned duties” (ibid).
Open science is also science done through care and kindness: science that much more resembles the model of peer production within a commons, than it does a winner-take-all corporate struggle. “[W]ithout receiving conventional, tangible payments or favors in return, peers exercise kindness, benevolence, charity and generosity” (Benkler and Nissenbaum 2006). Open science demands new levels of response-abilities: based on new and expanded academic freedoms (See: Values, freedoms and principles) and internet-enabled collaborations grounded in what Fitzpatrick (2019) calls “generous thinking.”
“This is generous thinking: listening to one another, recognizing that we have as much to learn as we do to teach, finding ways to use our collective knowledge for the public good. From the broadest rethinking of our political and institutional landscape, to developing new ways of working in public, to sharing our ways of reading, to focusing on the most intimate practice of listening — at each level, we must be connected to, fully part of, the world around us” (Fitzpatrick 2019).
Generous thinking expands here, emerging out from the university to help heal the troubles of the surrounding communities through active caring, and also to grow publics that can continue the work of caring outside the academy and among themselves.
There are a lot more articles and books about the history of kindness and care that point out how these virtues were heralded as the basis of human happiness for centuries, and only recently (last 3-400 years) have these been eclipsed by more individualistic moral models (thanks to Hobbes, Kant, etc.—the usual suspects). So… practicing open science may also be good for your happiness. Doing open science can improve your happiness, and the happiness of those around you. How about that?
“Through the power of onlyness, an individual conceives an idea born of his narrative, nurtures it with the help of a community that embraces it, and, through shared action, makes the idea powerful enough to dent the world” (Merchant 2017)
When we look ahead at some near-future, open-science-based academy, we can point to a new science workplace solidly anchored into its own logic, with internal values that reveal its core practices. Each open organization operationalizes these values locally.
Open science is aspirational because science is hopeful: it aspires to add significant new knowledge to human understanding. The open-science movement started with open access to research results. This struggle continues. The current pandemic may accelerate this process. Next, open science needs to move to implement cultural practices that enable Demand Sharing and Fierce Equality at all levels and organizations. Certain common notions about academy practices—certain notions inherited from decades of science infested by toxic cultural habits and perverse incentives—will need to be interrogated as open science looks to open cultural practices to shape how it changes in the future. Let’s examine some of these practices.
But first. The notion of, and the term “onlyness,” is from Nilofer Merchant* (2017), an entrepreneur/business consultant (See also: <https://nilofermerchant.com/>; Accessed May 12, 2020). Merchant penned this term to highlight how the quality of ideas in any group springs from the distinct contribution that each person can bring into conversation, when they speak from the totality of their own knowing and being (See: Knowing and conversation). She then outlines how to optimize for this potential. Most teams and organizations downplay, or worse, prohibit, this potential, asking team members to be flexible generalists and leave their individual genius at home. They ask their members/employees to “fit in” instead inviting them to belong on their own terms.
By locating “diversity” and “inclusion” in the distinct features of each individual, Merchant re-places the standard arguments for these values within teams and organizations. No tokenism permitted here. Instead, we find a keen respect for the distinct biographies of learning and knowing carried by each person in their whole being. As Merchant (2017) notes; “To claim yourself as whole is to assert your own value—not because everything about you is perfect but because it is all perfectly yours. This acceptance of your full self is nonnegotiable in claiming the power of onlyness. If you can’t value what you alone have to offer, no one else can either.”
Onlyness belongs to every individual to the extent they make a claim about it. It is not exclusive or elite; not just a property of egoistic narcissists. It does not automatically lead to assholish behaviors. It is not acquired from membership in a population cohort or a generation, even though it is socially attuned. It is informed throughout your biography, and includes what you alone can bring to your family, your society, and the planet. Einstein’s housekeeper had as much onlyness as did Einstein, only Einstein managed to explore and mine his to the advantage of his ability for creative insight.
Very much in line with recent theories of organizational knowledge management (See: Demand sharing and the power of pull), onlyness powers innovation and creativity within teams and projects by surfacing insights across vital conversations. This also amplifies the value of networks over hierarchies. Open innovation studies have shown that “marginal individuals” contribute significantly to solving grand challenges online, in part, by reframing the problems: “The ability of marginal individuals, with different perspectives and heuristics, to come up with novel solutions to broadcast problems, indicates that they may be conceiving of a given problem in a different way than the seeker. Thus problems should not be considered as fixed and given but open to redefinition by the solvers themselves” (Jeppesen and Lakhani 2010). Each team member has a contribution to make to this conversation. No more deference to the highest paid person in the room. Are you looking for better conversations (of course you are), then help each person in your research network explore and claim their onlyness.
“[T]he new research suggests that our everyday thinking and learning is strikingly continuous with scientific thinking and learning. The pre-schoolers see probabilistic evidence and revise hypotheses, but they don’t necessarily know that that is what they are doing—nor indeed do ordinary adults” (Gopnik 2012).
There is no textbook sufficient to map the individual’s journey into science. There is no common, model individual open scientist: no career best practice, no business-school recipe for success can identify which scientist will excel in their research endeavor. There is no “mold” for an open scientist. Like a concert violinist, a scientist must master techniques and become proficient in their practice and precise in their methods. But that’s more like saying they’ve stopped being children and are now adults. Or, in a curious fashion, that they’ve stopped trying to be so adult, and have opened up their internal child-driven curiosity and wonder. To be an open scientist, as Berger (2014) notes: “We must become, in a word, neotenous (neoteny being a biological term that describes the retention of childlike attributes in adulthood). To do so, we must rediscover the tool that kids use so well in those early years: the question.”
Knowing what the best questions are and how these are situated into the landscape of scientific discovery is the admission price to enter the “knowledge club” (Accessed May 18, 2020) of science. The other side of wonder is rigor. Rigor is learned later in school. You cannot have wonder without rigor. The reverse is also true. “[R]igor cannot be sustained without wonder; and without both capacities, creativity—and innovation—will suffer” (Nixon 2020). However, rigor is not what drives the individual capacity for science. It’s a launch utility, not a fuel. You can teach methods and you can learn content. That gets you to the door of science. To open it, you need to apply your own brand of onlyness.
“It was opal and this was something I knew, something I could draw a circle around and testify to as being true. While looking at the graph, I thought about how I now knew something for certain that only an hour ago had been an absolute unknown, and I slowly began to appreciate how my life had just changed.
I was the only person in an infinite exploding universe who knew that this powder was made of opal. In a wide , wide world, full of unimaginable numbers of people, I was—in addition to being small and insufficient—special. I was not only a quirky bundle of genes, but I was also unique existentially, because of the tiny detail that I knew about Creation, because of what I had seen and then understood” (Jahren 2016).
Onlyness here means deep and broad individuality and intellectual curiosity: open scientists are deep into their own specific passion and love for some aspect of science, and their own corner of the unknown in the infinite play of science. Anyone who has completed a dissertation knows the onlyness—and also the loneliness—of understanding something deeper than their books, better than their advisors, and newer than anyone else. Open scientists are also broad enough in their sense of how science works and in the landscape of methods and literature to see the larger picture of open science practice shared in their discipline and beyond.
Onlyness is the reason why scientists can uncover astonishing new insights. By “scientists” here, we mean all students of science, all members of a science team (data nerds, technical specialists, grad students, and principle investigators), in fact, all people on the planet who find that their curiosity—and their own life-to-right-now—has moved them to a distinct point of understanding: “You’re standing in a spot in the world that only you stand in, a function of your history and experiences, visions, and hopes. From this spot where only you stand, you offer a distinct point of view, novel insights, and even groundbreaking ideas. Now that you can grow and realize those ideas through the power of networks, you have a new lever to move the world” (Merchant 2017). Onlyness is why your dissertation nearly drove you insane, since it required you to dive deep into a personal journey of discovery that now means you know more—and you know differently—from anyone else on the planet.
If professional scientists act similarly, this similarity comes from the shared depth of their appreciation for the “role of ignorance and the importance of uncertainty” in science (See: Brain Pickings; Accessed May 5, 2020). Rather like we all are in the current situation (now being May of 2020), scientists are, and have always been, alone, even when together.
Institutional prestige is a profound drag on the potential for networked science. If your administration has a plan to “win” the college ratings game, this plan will only make doing science harder. It makes being a scientist less rewarding. Playing finite games of chasing arbitrary metrics or bullshit prestige drags scientists away from the infinite play of actually doing science. In a world where science happens elsewhere, the first thing your campus can do is become more attached to all those academy “elsewheres” that can amplify your in-house efforts.
The best thing your campus can do is to became that really attractive “elsewhere” to which others want to attach themselves. This means opening up to demand sharing. Once science gets funded across a broad spectrum of institutions and across the globe, online collaboratives will form, and work together, and create new knowing without regard to game-able institutional rankings. The entire academy will become more nimble, creativity will quicken, and good work will find its rewards outside of current reputation schemes.
“One will weave the canvas; another will fell a tree by the light of his ax. Yet another will forge nails, and there will be others who observe the stars to learn how to navigate. And yet al.l will be as one. Building a boat isn’t about weaving canvas, forging nails, or reading the sky. It’s about giving a shared taste for the sea, by the light of which you will see nothing contradictory but rather a community of love” (Saint-Exupéry 1948; translation: <https://quoteinvestigator.com/2015/08/25/sea/>; Accessed May 11, 2020).
The future of open science will be much more distributed and democratic. Open scientists work wherever their research and teaching acumen is needed and supported. The perverse lure of bullshit-prestige institutions disappears as great work emerges from highly diverse teams in hundreds of institutions and locales across the planet, and along the internet.
Instead of boasting of their employment at some famous university or lab, open scientists and their in-house and online teams are deep into infinite play wherever they are employed. They shape the culture of their teams, bending this toward fierce equality and demand sharing. Their combined onlynesses serves to push the team effort beyond what any one of them might do. They fill open repositories with new data and findings. They care for their work together, and for each other as people. They celebrate their team culture. A great team in a sad organization with a toxic culture works better than a sad team in a great organization.
The notion that a university can increase managerial control over research practices using performance-based funding schemes, and so to capture year-by-year productivity gains, has been tried in various places on the globe. But the practice of top-down, goal-driven, productivity management translates poorly from the commercial world (where this is also failing) into the academy. Metrics applied in this manner are highly susceptible to Goodhart’s law, and subsequent gaming attempts. The best incentives for better science are those goods internal to the professional practices of doing science. The best way to improve on these is to support governance practices that open up more avenues for sharing and knowing.
There is an authentic “meritocracy,” here, not the artificial sort claimed by prestigious organizations. A fluid, dynamic, emergent shared sense of where new knowing is being forged. In the interconnected intellectual rooms of online science communities, the acceleration of knowing and discovery through access to open shared resources, active, global collaborations, and diverse team-building assembles shared intelligence to solve wicked problems. There is no organizational strategic plan, no business model, no tactical hiring that can match open innovation collaboratives that push the boundaries and change the rules of their infinite playing together. The merit belongs to the team, and to the work. What the scientists get is the joy and wonder of a lifetime of science play.
Doing open science gets a boost when the culture of open science is shared and celebrated at the top level of academy institutions—whether its a college, a university, a learned society, or a science agency. Under these circumstances, institutional values and their shared meanings cascade down across all departments, labs, and teams. With solid, top-level institutional support, teams build their own shared mini-cultures to encourage caring and rigor.
The cultural project of open science is actually quite small. As much as open science is just “science done right” and a “return to former science norms,” the professed culture of most science organizations really only needs to be rearticulated for open science use, and celebrated as an active, reflexive cultural layer (See above). Goals are left to teams to identify and activate for themselves.
All biographies of “notable scientists” spend a great amount of their content describing the onlyness of these individuals (without calling it that). Every “genius” you read about is someone who managed to tap into their onlyness and find insights into infinite play (which is commonly referred to as a “serendipitous” event). Every one around them—these individuals are nearly always surrounded by colleagues—contributed to these conversations. They need to noted too.
“In the end, it cannot be doubted that each of us can see only a part of the picture. The doctor sees one, the patient another, the engineer a third, the economist a fourth, the pearl diver a fifth, the alcoholic a sixth, the cable guy a seventh, the sheep farmer an eighth, the Indian beggar a ninth, the pastor a tenth. Human knowledge is never contained in one person. It grows from the relationships we create between each other and the world, and still it is never complete” (Kalanithi 2016).
No scientist has ever refused a Nobel Prize. (NOTE: Two people have declined this. Jean-Paul Sartre did, because he was Sartre. And, Le Duc Tho did, because his award was shared with Henry Kissinger, who supported bombing Hanoi during Christmas.) Learned societies and professional academic groups offer a wide range of honors that scientists gladly accept (usually along with travel support to a meeting they would like to attend). Other honors come directly from universities or funding agencies. All of these honors fatten résumés and grease promotion portfolios around the planet.
Scientists crave the economic support they need to do the work they love. If they can translate honors into cash, they will do so. And yet, should these particular honors stop being awarded, there is little to indicate that science would be less rewarding or less able to track the value of science work. Open science offers to expand opportunities to find and use great science. New methods of acknowledging the work of scientists and teams, and also the provenance of research can replace or enhance how scientists get connected to each other through their work.
Great work in open science can be found anywhere on the planet, and also within any team working in an open-science organization, small or large. The gifts of new knowledge are freely shared, but they also obligate others to pay attention. applaud their value, and scorn those who seek attention for their own finite game. This is central to the culture of demand sharing. Recognize the work. Applaud the teams, the history, and the ideas. Show appreciation for how this knowledge is shared, without needing to pin this discovery on an individual scientist.
“Scientists are like those levers or knobs or those boulders helpfully screwed into a climbing wall. Like the wall is some cemented material made by mixing knowledge, which is a purely human construct, with reality, which we can only access through the filter of our minds. There’s an important pursuit of objectivity in science and nature and mathematics, but still the only way up the wall is through the individual people, and they come in specifics—the French guy, the German guy, the American girl. So the climb is personal, a truly human endeavor, and the real expedition pixelates into individuals, not Platonic forms. In the end it’s personal, as much as we want to believe it’s objective” (Levin 2016).
Growing and tapping into your onlyness is not just a trait that the best open scientists share, it’s a trait that open science needs to support, to grow, and to reward. Open science is the common work of millions of un-common individuals. The education of an open scientist requires a healthy dose of infinite-game training, the unleashing of purpose and imagination, and courage and caring in service of collective knowing. In the end, it is the research goal that becomes the teacher, and every scientist plays this alone, even within their team. Each scientist contributes the difference they have cultivated in their own insights to the collective knowing of their team.
To help your students develop their onlyness requires that you promote in them the courage to be essentially different from those around them, and also the honesty and humility to recognize the onlyness of others. Mainly you do this by working on your own onlyness and showing how this matters. You cement your knowledge on the wall of science, daring your students to step up to a new level through you. You share conversations with them that provoke responses only they can provide. Be open to learn from their knowing.
Several authors in the past decades—from Foucault and Illich to Robinson and Godin—have pointed out that factory-style schooling diminishes onlyness (without calling it thus) in favor of standardized understandings and personal disempowerment. Open science will need to also work on the cultures of learning and teaching science. Like practical wisdom (See: The practical wisdom of doing science), onlyness needs to be exercised for it to grow.
Merchant’s work on onlyness was designed to help companies become more creative and innovative through the collective conversations of their employees, powered by an organizational culture that welcomed each of them to belong to these conversations in their wholeness. What she offers to businesses holds true for the academy, and most particularly in the academy, where onlyness powers great science through networked collaborations.
Many thanks for Nilofer Merchant’s comments on a draft of this section.